Patent Application
20220374946
This disclosure generally relates to a grading and authenticating system and method of using the same. More particularly, the disclosure relates to a computerized system for grading and authenticating sport and non-sport card collectibles and other printed objects including event ticket, event programs, photographs, photograph facsimiles, brochures, and the like.
Card collecting, including sport and non-sport cards, has become, for many fans, much more than a hobby. There is a great deal of potential value in building a card collection and it could take years of research, time, and work. When a collector is interested in building a valuable card collection, it is very important for the collector to know that the condition of the card, or collectible, significantly affects its value as a collectible. That condition is a very important component of a collectible's vale, is generally understood by experienced collectors within the industry but less so, if at all, by new entrants into the industry. As such, it is very common for cards, as well as other collectible objects, to be professionally evaluated by industry recognized experts and graded in an effort to determine the condition and provide a basis of the value of a particular card or object. A professionally graded card is inspected for authenticity and rated on various criteria, for its condition. The card is then assigned an overall grade, generally from 1-10, sealed in a tamper-proof holder (slab) and assigned a certification number that is affixed to the holder (slab) and maintained by the grading company. A graded card can increase the value of the card in comparison to an ungraded card of equal or similar condition by means of offering the card owner or buyer a third-party assessment of the card's authenticity and condition.
Grading cards is based on various characteristics that, with respect to manual grading, pertain to the “general eye appeal” of the card. Characteristics of the card that are universally examined in the grading process are centering, corners, edges, and surface. Centering is the placement of the image (top to bottom and left to right) on the card relative to the entire card. Industry standards exist for percentage of off centering variance permitted for top to bottom and left to right, for each of the possible card grades. The corners of the card are inspected to determine the quality of the physical condition of the corner and/or if any defect of the corners is present. Corner defects generally include at least one of, corner fill, corner fray, corner lift, corner angle, and corner surface wear. The edges of the card are examined, similarly as the corners, to determine the quality of the physical condition of the edges of the card, and with precise measurement account for any damages and/or imperfections along the edges. The surface of the card is examined with precise measurement to account for any damage and/or imperfections on the card, such as scratches, creases, tears, pinholes, stains, dents, attempts at recoloring, tampering with the card stock, and alterations of the card stock, etc.
Corner fill is any missing card stock in an area pre-determined by the manual grader of the card to be the corner area.
Corner fray is wear on the card within the manual grader pre-determined corner area that is not worn enough to remove all of the corner stock beneath the fray within the area.
Corner lift is where the stock of the card is raised from what would be the flat surface determined by the manual grader from the overall surface of the card.
Corner angle is how much variance exists between the actual card corner angle and 90 degrees for each of the four corners on a rectangular shaped card. When the card is not rectangular, the variance is measured as the actual angle of each corner (three for a triangle shaped collectible and five, or more if the card has more than four corners) and the angle) that is determined by the manual grader to be the correct angle.
Corner surface wear is the measurement of a defect on the edge of the card within the area of the card pre-determined by the manual grader to be the corner area.
Today there are numerous grading companies, three of which that represent an estimated 95+% of the market. Each of the grading companies grade cards by human evaluation, primarily with the naked eye or an eyepiece that is generally 7.5 to 15 times magnification. Manual grading is not accurate, consistent, or reproducible. Manual grading may not be accurate because the same card when graded manually, by two or more grading companies, may get a different grade for each time the card is graded. Manual grading may not be consistent because two different cards with the same or identical defects may get different grades from the same grading company. Manual grading may not be reproducible because the same card, when graded two, or more, times by the same grading company, may get different grades for each card graded. We estimate that a grading company grading 9 million cards per year, with 115 graders, working 21.5 days per month for eight hours per day, spends 37 seconds per card on the average. We also estimate that a grading company It is estimated that manual grading companies typically devote approximately one minute per card during the grading process. Because this grading process can be highly subjective, it results in cards rarely receiving the same grade when graded by any of the three industry leaders, or the same grade when re-graded with the same grading company that previously graded the card. As such, there is no grading methodology available in the marketplace today that provides accurate and consistent results in cards as well as other collectibles, e.g., coins, stamps, etc.
Grading is, with extremely rare exception, the most significant determination of value, such fluctuations in grading often result in misstatement of value and lack of confidence in the marketplace necessary to sustain a stable and efficient market. All of the grading companies solicit resubmission of any previously graded card in its original holder (slab) by other companies or even graded by themselves for the possibility of a higher grade.
Awareness in the marketplace of the possibilities for resubmitted cards receiving higher grades has resulted in card owners breaking open the “tamper proof” holders and resubmitting the cards multiple times, if necessary, without disclosing that the card has been previously graded.
The variance in grades for resubmitted cards combined with the subjective and inconsistent card grading process itself results in creating a lack of confidence in the marketplace necessary to sustain a stable and efficient market.
The present process utilized in the grading industry creates opportunity for larger collectors (e.g. larger customers of the card grading companies) to manipulate the current system's subjective grading to their advantage by re-submitting cards for a higher grade based upon natural human variability or their influence as a large customer. Small collectors lack sufficient size to “influence” card grading and often sell cards at lower prices due to the lower grades they receive.
Without an accurate and consistent grading system in place, there are no means of preventing grading companies and/or their larger customers from exploiting grading subjectivity and doing so at the expense of the small card buyer and seller. The “small” card buyer represents the overwhelming majority of card ownership but disproportionate minority of ownership of card value. This small collector is an entry-level hobbyist, for example, a young child who buys cards of his “hero” before the youngster becomes a collector.
The collectible market's dysfunction is facilitated by a lack of applying modern visual technology and computer processing capabilities. Grading today (by hand and by eye) while traditional, is unfair, inconsistent, and has high labor content, relative to the disclosure, which is directed to a computerized grading and authentication system and method.
The disclosure is a computerized system and method for objectively grading and authenticating collectibles. The disclosure is configured to objectively grade and authenticate collectibles at a higher reliability and consistency, by using a finer resolution than is possible with the human eye. The present disclosure addresses these needs and provides further related advantages.
The disclosure provides various aspects of a computerized system and method for grading and authenticating collectibles, wherein the condition and quality of an image and the material upon which that image is placed, is a component of value as determined by the market. The disclosure provides a computerized system and method to objectively grade and authenticate collectibles. The disclosure eliminates the subjectivity present in the human grading process and overcomes the inherent limitations of the human eye.
In one aspect of the disclosure, as broadly described herein, a computerized system is disclosed that grades and authenticates collectibles, comprising an image acquisition device and a computer system. The image acquisition device comprises a housing defining an internal space, an imaging device, at least one light source to illuminate at least part of the internal space, and a stage, wherein the stage is within the housing and receives a collectible. The computer system comprises at least one processor, and at least one output device, wherein the image acquisition device is configured to receive an input signal from the computer system. The image acquisition device is configured to transmit at least one output signal to the computer system. The at least one processor applies at least one image processing routine to the at least one output signal received from the image acquisition device such that the at least one processor produces grading information and transmits the grading information to the at least one output device.
In another aspect of the disclosure, as broadly described herein, a method for grading and authenticating collectibles comprising, capturing at least one image of a collectible, transmitting the at least one image to at least one processor, applying at least one image processing routine to the at least one image, producing grading information based on results of the at least one image processing routine, and transmitting the grading information to at least one output device.
In another aspect of the disclosure, as broadly described herein, a system for grading a collectible is provided herein. The system comprises a grading apparatus configured to receive at least one image of the collectible. The grading apparatus is configured to apply at least one processing routine to the at least one collectible. The grading apparatus is configured to generate a grade report of the collectible based at least one results of the at least one processing routine. The system comprises an encasing apparatus configured to encase the graded collectible within a protective slab.
In another aspect of the disclosure, as broadly described herein, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a device for grading a collectible. The apparatus may receive at least one image of the collectible. The apparatus may apply at least one processing routine to said at least one image. The apparatus may generate a grade report of the collectible based at least on results of the at least one processing routine.
This has outlined, rather broadly, the features and technical advantages of the disclosure in order that the detailed description that follows may be better understood. Additional features and advantages of the disclosure will be described below. It should be appreciated by those skilled in the art that this disclosure may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the teachings of the disclosure as set forth in the appended claims. The novel features, which are believed to be characteristic of the disclosure, both as to its organization and method of operation, together with further objects and advantages, will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the present disclosure.
The disclosure described herein is directed to different aspects of a computerized system and method for grading and authenticating collectibles, such as but not limited to sports cards, non-sports cards, coins, stamps, photographs, facsimile photographs, autographs and the like. The detailed description set forth below, in connection with the appended drawings, is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the various concepts. It will be apparent, however, to those skilled in the art that these concepts may be practiced without these specific details. In some instances, well-known structures and components are shown in block diagram form in order to avoid obscuring such concepts. As described herein, the use of the term “and/or” is intended to represent an “inclusive OR”, and the use of the term “or” is intended to represent an “exclusive OR”.
The disclosure uses an image acquisition device that can acquire one or more high resolution images of a collectible with detail that is at a higher resolution than that of the naked eye. The high resolution images of the collectible provide an enhanced degree of detailing of the collectible than is possible with the naked eye. The image acquisition device can also be configured to examine the physical condition and/or characteristics of the collectible to determine if the collectible has been altered and/or modified. The one or more high resolution images are processed using one or more image processing routines for the purpose of gathering all data applicable to making a determination of the authenticity, condition and grading of the collectible. Through the application of image processing, an analysis and evaluation of specific criteria can be provided resulting in a more consistent, reproducible, and objective grade for collectibles being established.
The disclosure can be utilized to obtain detailed information about the collectible that is not done currently with conventional human grading systems. For example, the detailed information obtained allows the disclosure to quantify the amount of any damage present in the collectible, if the collectible has been altered from its original condition, or if the collectible has been modified in an attempt to repair and/or conceal defects. These alterations and/or modifications can be imperceptible to the human eye and can result in the human grader assigning an inaccurate grade to the collectible, which thereby improperly inflates and/or distorts the value of the collectible. Furthermore, although it may be possible for the human grader to identify the presence of some of the damage in the collectible, the human grader cannot quantify the amount of such damage present in the collectible nor evaluate with a consistent standard from grading company to grading company, individual grader to individual grader, or card to card. Conventional human grading systems are outdated, inaccurate and distort the values of the collectible market.
Additionally, the lack of sophisticated grading systems creates the opportunity for the counterfeiting of collectibles. Counterfeiting is very prevalent in the collectibles marketplace and the disclosure can assist in detecting and thereby minimizing or even eliminating counterfeiting and/or fraud in the collectibles marketplace due, in part, to the disclosures ability to examine the collectible in high resolution, beyond what is capable with the human eye and the eliminate the variances of interpretation of what is being seen by the human eye and is incorporated in the manual grading process.
Counterfeit cards can be fabricated in modern times that attempt to pass for originals. The quality of counterfeit cards has increased over time such that only a trained expert can identify a counterfeit, and if so, only on occasion. However, a counterfeit card that has escaped one expert examination and is placed in the tamper-proof holder or slab, a complete and unobstructed access to the card is limited by the tamper-proof holder to future expert examination. This inability to detect a counterfeit card on first manual grading examination encourages the industry to continue to attempt to get counterfeit cards graded. Even worse, when a counterfeit card is determined to exist after being manually graded and slabbed, the industry loses confidence, suspects collusion and insists that the counterfeit slabbed card is the result of “influence” of the people who submit the highest volumes for grading to the manual grading companies. The disclosure utilizing high resolution images of the card within the tamper-proof holder can determine whether the card is counterfeit prior to placing the card in a slab. Also, the disclosure, through the application of image processing and a comparative analysis of known genuine cards with a card being authenticated and graded by application of proprietary algorithms of the disclosure can determine if the slabbed card is a counterfeit on a more consistent basis than otherwise determined by a manual examination.
The disclosure is described herein with reference to certain aspects, but it is understood that the disclosure can be embodied in many different forms and should not be construed as limited to the aspects set forth herein. In particular, the disclosure is described herein in regards to a computerized system and method for grading and authenticating collectibles, but it is understood that the disclosure can evaluate and/or examine non-collectible items wherein authenticity and/or legitimacy of a non-collectible item is desired.
Although the terms first, second, etc. may be used herein to describe various elements or components, these elements or components should not be limited by these terms. These terms are only used to distinguish one element or component from another. Thus, a first element discussed herein could be termed a second element without departing from the teachings of the present application. It is understood that actual systems or fixtures embodying the disclosure can be arranged in many different ways with many more features and elements beyond what is shown in the figures.
It is to be understood that when an element or component is referred to as being “on” another element or component, it can be directly on the other element or intervening elements may also be present. Furthermore, relative terms such as “between”, “within”, “below”, and similar terms, may be used herein to describe a relationship of one element or component to another. It is understood that these terms are intended to encompass different orientations of the disclosure in addition to the orientation depicted in the figures.
Aspects of the disclosure are described herein with reference to illustrations that are schematic illustrations. As such, the actual thickness of elements can be different, and variations from the shapes of the illustrations as a result, for example, of manufacturing techniques and/or tolerances are expected. Thus, the elements illustrated in the figures are schematic in nature and their shapes are not intended to illustrate the precise shape of a region of a device and are not intended to limit the scope of the disclosure.
The computerized system 100 comprises an image acquisition device 102 and a computer system 104. The image acquisition device 102 comprises an imaging device 106, a housing 108 defining an internal space 110, a stage 112, and at least one light source 114 to illuminate at least part of the internal space 110, wherein the stage 112 is within the housing 108 and receives a collectible 116. The computer system 104 comprises at least one processor 120 comprising processor-executable computer instructions and at least one output device 122, wherein the computer system 104 is configured to transmit one or more control signals to the image acquisition device 102.
The housing 108 comprises a base 109, a top 111, and a plurality of sidewalls 113, wherein the base 109 and top 111 are coupled to the plurality of sidewalls 113 such that the base 109 is opposite the top 111. The base 109, top 111 and plurality of sidewalls 113 define the internal space 110 of the housing 108.
The stage 112 is disposed within the internal space 110 of the housing 108 and provides a support surface 115 to receive the collectible 116. The positioning of the support surface 115 within the housing 108 is adjustable to any height within the internal space 110. In some aspects, the support surface 115 can also be adjusted about one or more axes, such that the support surface 115 can be angled with respect to the imaging device 106, at least one light source 114 or a combination thereof within the internal space 110.
An imaging device 106 is adapted to capture at least one image of the collectible 116. The at least one image of the collectible 116 captured by the imaging device 106 is a high resolution digital image of the collectible 116. The high resolution digital image is a digital representation of the collectible 116 and is processed using at least one image processing routine to determine a grade of the collectible 116 based on a set of technical grading criteria. In one aspect, the imaging device 106 can be a high resolution digital camera, such as but not limited to an 18 megapixel digital camera. However, the imaging device 106 is not intended to be limited to an 18 megapixel digital camera, and could have a resolution that is higher or lower than 18 megapixels. In addition, the imaging device 106 is not intended to be limited to a digital camera. When the imaging device used is a camera, the camera within the housing 108 is adjustable to any height within the internal space 110 to increase or decrease field of vision. In other aspects, the imaging device 106 can be a scanner or other imaging device that can create a digital image or other reproduction of the collectible 116.
In aspects wherein the imaging device is a scanner, the scanner can be physically isolated from or replace and/or supplement the housing 108 and can have its own self-contained stage 112, internal space 110, at least one light source 114, and a sensor to capture the image of the collectible on the surface. Such a scanner device is intended to be understood as an alternative or supplement in any description of the system herein. One example of a scanner can be a flatbed scanner. However, the scanner, or multiple scanners, can be arranged in many different known configurations, and is not intended to be limited to a flatbed-like scanner.
In aspects that utilize a digital camera as the imaging device, the collectible 116 is arranged on the surface 115 of the stage 112, such that the collectible fills approximately 90% of the camera's field of view. With an 18 megapixel digital camera, for example, this results in approximately 1200 pixels of resolution per inch of a typical 3.5″×2.5″ collectible card. A higher resolution camera would, in turn, yield a higher-resolution image. In other aspects, the collectible can be arranged to fill more or less than the camera's field of view and is not intended to be limited to 90%. This above 1200 pixels per inch is an example of what could be considered high resolution for any imaging device 106 of the image acquisition device 102, and is not intended to be limited to aspects that utilize a digital camera. The above also applies to other imaging devices, such as but not limited to a scanner. The imaging device 106 can obtain an image of the collectible 116 in varying pixels of resolution per inch. For example, the pixels of resolution per inch can start from at least 300 pixels per inch and increase as desired. However, this example is not intended to be a baseline that needs to be met in order to qualify as high resolution. Images having 300 pixels per inch is generally accepted in digital photography as being high resolution images.
In some aspects, the imaging device 106 may capture a plurality of images of the collectible 116. In such instances, the plurality of images may be processed to generate a topological image of the collectible. The topological image of the collectible may comprise a plurality of images of the collectible. The plurality of images of the collectible may comprise a series of images of the collectible lighted under different lighting conditions. One or more surface imperfections on the collectible may be identifiable using the topological image. In some aspects, at least one processing routine may be utilized to generate the topological image. The topological image may be used to identify one or more defects on the collectible. The topological image may be used to score the identified one or more defects. In some aspects, the topological image of the collectible may be overlaid onto the at least one image of the collectible. An opacity of the topological image of the collectible may be adjustable as overlaid onto the at least one image of the collectible and may be used to identify one or more defects. The topological image may be used to score the identified one or more defects. In some aspects, the opacity of the topological image may be adjusted to allow one or more surface imperfections on the collectible identified using the topological image to be compared against the at least one image of the collectible. The one or more surface imperfections may comprise a card stock manipulation, wherein the topological image may identify one or more variations in a surface topology or thickness of the collectible based on an expected surface topology or thickness of the collectible. In some aspects, the topological image may be displayed on the at least one output device 122 to allow for a comparison between the topological image and the at least one image of the collectible. In some aspects, the topological image may be used by the system to identify defects on the collectible, scoring the identified defects, and to grade the collectible. A series of individually-lighted images from multiple sides of the collectible may be captured using photometric, stereoscopic imaging, then composited into a single image to highlight variances in surface topology, in order to generate the topological image. The position and angles of applied lighting may be specifically attuned to the collectible to ensure that micron-level variances and/or defects in a surface topology of the collectible may be detected through the compositing of all such individually lighted images. In addition to the compositing methodology, a series of image processing techniques may be applied that incorporate such methods as Quantize, Grey Morphology Median NxM Filtering and Convolve. The topological image may be further processed and analyzed with a combination of machine learning and object profiling techniques to identify and/or classify specific surface defect types. The topological image generated may be capable of identifying surface defects, such as but not limited to scratches, pits, dents, print lines, roller marks, wrinkles, creases, print defects, stains, ink defects, surface wear, card thickness variations, or the like. In some aspects, the topological image may be utilized, by the system, to identify micron-level variations in a surface topology of a collectible or collectible thickness. The resulting thickness data may be utilized to evaluate whether or not some form of card pressing or other relevant card stock manipulation has occurred, based on specific variation from the collectible's expected thickness.
In one aspect, as shown in
For example, in the aspect of
However, in other aspects, the imaging device 106 can comprise physical dimensions that are less than or similar to the opening of the top 111. The imaging device 106 can be configured to be externally disposed with respect to the internal space 110 of the housing 108 in order to capture the at least one image of the collectible 116. In other aspects, part of the imaging device 106, for example a lens body, at least partially extends into the internal space 110 of the housing 108 in order to capture the at least one image of the collectible 116.
The housing 108 is configured to block penetration of exterior light into the internal space 110, which prevents exterior light from altering the lighting condition of the internal space 110. It is important to prevent and/or limit exterior light from entering the internal space 110 because exterior light could impinge on the collectible 116 and/or alter the pre-defined lighting condition, which could affect the accuracy of the grading of the collectible 116. At least one advantage of the disclosure is that the grading of a collectible is repeatable or reproducible with very accurate and consistent results. This is due, in part, to the high resolution images captured by the imaging device 106 under controlled pre-defined lighting conditions. However, in other aspects, exterior light may enter the internal space 110 of the housing 108 such that images captured by the imaging device 106 in the presence of exterior and/or uncontrolled light are acceptable for grading.
The housing 108 further comprises at least one light source 114 to illuminate at least part of the internal space 110. The at least one light source 114 can be configured to provide a plurality of different lighting conditions, wherein the imaging device 106 captures an image of the collectible 116 under each of the different lighting conditions. The plurality of different lighting conditions accentuate the physical condition of the collectible 116 in order to detect defects and/or imperfections. For example, an indentation, scratch or crease on the collectible can cause a shadow under certain lighting conditions and the shadow can be examined to determine the extent of the indentation, scratch or crease. This is an example of the lighting conditions assisting in identifying a defect, and neither the invention nor the defects identified are intended to be limited to such examples. In some aspects, the at least one light source 114 may be configured to capture all areas of the collectible and/or to be adjusted such that various sides of the collectible may be at a focal point of the at least one light source. The light emitted from the at least one light source may be varied such that angular lighting reduces refraction that might otherwise interfere with the lighting required to capture the image in the manner that attribute scoring will be accurate, consistent, and reproducible.
The at least one light source 114 is positioned within the internal space 110 in order to provide the different lighting conditions. In the aspect of
In some aspects, the system may be configured to apply one or more lighting conditions to the collectible, such that the one or more lighting conditions may assist to identify one or more defects on the collectible. In some aspects, the one or more lighting conditions may comprise at least one of a refractive light from one or more different angles. In some aspects, the one or more lighting conditions may create one or more shadows on the collectible. The one or more shadows may be measured to identify raised or depressed surface areas on the collectible. In some aspects, the one or more lighting conditions may comprise infrared (IR) lighting. The IR lighting may be configured to measure a thickness of the collectible. In some aspects, the one or more lighting conditions may create one or more shadows on the collectible, such that the at least one image, individually, or a compositing of a plurality of images, may be measured to identify raised or depressed surface areas of the collectible. In some aspects, stereoscopic photometric imaging with refractive light from different angles may be utilized to create a series of simultaneous images to establish a composite image that takes advantage of refractive light conditions on the surface to measure and identify type, number, size, and location of all surface defects.
In yet other aspects, as shown in
For the same or similar elements or features, the same reference numbers will be used throughout the application herein. In the aspect of
The light sources 114 can comprise many different types of light sources, such as but not limited to, incandescent, fluorescent, light emitting diodes (LED), and the like, or a combination thereof. In the aspects of
The housing 108 can comprise many different materials and/or many different configurations. For example, in the aspect of
In some aspects, as shown for example in the diagram 2200 of
In some aspects, as shown in the diagram 2400 of
In some aspects, the system may be configured to deionize the collectible to remove one or more particles from the collectible and balance an ion level on the collectible. The deionized collectible may prevent the one or more particles from being attracted to the collectible, or being on the collectible when the one or more images are captured. In some aspects, deionizing the collectible removes the one or more particles from a region between the collectible and an image acquisition device. A static charge on the collectible, without deionizing, may attract particles, dust, and other airborne artifacts to the surface of the collectible. By utilizing an air ionizer (e.g., a pencil-type air ionizer), the system may remove all particles from the surface of the collectible and balances the ion level on the collectible so that it does not continue to attract these particles.
The disclosure is not intended to be limited to the configuration and/or the number of light sources 114 disclosed in the aspects of
The computer system 104 comprises at least one processor 120 and at least one output device 122, wherein the computer system 104 is configured to transmit one or more control signals to the image acquisition device 102. The one or more control signals provide instructions to each of the at least one light source 114 and the imaging device 106. The computer system 104 transmits instructions via the control signal to the at least one light source 114 such that the at least one light source 114 provides a desired lighting condition in accordance with the instructions. The computer system 104 can also send a control signal to the imaging device 106 with instructions to capture an image of the collectible 116 after the at least one light source 114 is illuminating the collectible 116 under the desired lighting condition. The image acquisition device 102 thereby transmits an output signal to the computer system 104, wherein the output signal comprises the captured image of the collectible. In one aspect, the image acquisition device 102 can transmit the output signal to the computer system along the same connection that the image acquisition device 102 received the control signal from the computer system 104, while in other aspects, the output signal is transmitted from the image acquisition device 102 to the computer system 104 along a different connection. The connections between the image acquisition device 102 and the computer system 104 can be wired connections, wireless connections, or a combination thereof.
The computer system 104 can be configured to run a script comprising a series of instructions for the imaging device 106 and the light sources 114. For example, in one aspect, the script can comprise a sequence of actions wherein a series of control signals are transmitted to the imaging device or digital camera 106 and the light sources 114 such that the on/off state of one or more of the light sources 114 is activated/deactivated to provide one of a series of pre-defined lighting conditions, wherein the imaging device or digital camera 106 captures an image of the collectible 116 illuminated, if needed, in each one of the series of pre-defined lighting conditions, such that after each image is captured, the imaging device 106 transmits the captured image to the computer system 104, and the computer system 104 labels the image using metadata, exchangeable image file format (exif), and the like, and/or by naming the image filename to indicate the lighting condition under which the image was taken. This process repeats until an image has been captured under each of the series of pre-defined lighting conditions. The collectible 116 is stationary on the surface 115 and its positioning is not altered while the series of instructions are implemented by the light sources 114 and the imaging device 106. This results in each of the captured images being substantially aligned while illuminated under the different lighting conditions.
In one aspect, there can be nine different lighting conditions in which an image of the collectible 116 is to be captured. This will result in a set of seven to nine images of the collectible 116 in the seven to nine different lighting conditions. These images will then be processed and analyzed by the computer system 104 to determine a grade for the collectible 116. The disclosure is not intended to be limited to only seven to nine different lighting conditions. The disclosure can comprise more or less than seven to nine light different lighting conditions resulting in any number of images of the collectible.
In some aspects, the different lighting conditions can be provided by activating one of the light sources 114 and deactivating the remaining light sources 114, and repeats until each of the light sources has been activated individually. The number of captured images of the collectible 116 in different lighting conditions can be proportional to the number of light sources 114, or can be independent of the number of light sources 114. In other aspects, the different lighting conditions can be provided by activating a plurality of the light sources 114 and deactivating the remaining light sources 114. In such aspects, the intensity of light emission of the plurality of light sources 114 that are activated can be equivalent or different.
After the series of instructions has been completed, the collectible 116 can be repositioned, either automatically or manually, in order to capture images of another side of the collectible 116 utilizing the same and/or different series of instructions. For example, a collectible 116, such as but not limited to a baseball card, has a front side and a back side, such that when all the images of the front side have been captured, the baseball card can be automatically or manually turned over on the surface 115 to capture images of the back side. The lighting conditions for the back side of the card can be the same or different than the front side. For example, one side of the card can be glossy while the other side is not, such that different lighting conditions may be needed to give a proper grade. In one aspect, images of both the front and back sides of the baseball card under the different lighting conditions can be taken for the purpose of independently grading each side of the baseball card. The system may provide a single baseball card grade that includes the two or more sides or surfaces in instances where the collectible has multiple surfaces. However, in other aspects, images of only one side of the baseball card can be taken for the purpose of grading the baseball card. In yet other aspects, the collectible 116 can comprise a plurality of sides, wherein images of each of the plurality of sides can be captured in the different lighting conditions for the purpose of grading the collectible 116. However, in other aspects, images of at least one of the plurality of sides can be captured in the different lighting conditions for the purpose of grading the collectible 116. The collectible 116 can be repositioned manually to expose another side, while in other aspects, the repositioning of the collectible 116 could be automated. In yet other aspects, the image acquisition device 102 can comprise a plurality of imaging devices 106, such that the image acquisition device 102 can capture images of the top and bottom sides of the collectible 116 simultaneously, or without having to turn over the collectible to capture images of another side of the collectible. In such aspects, the collectible 116 can be interposed between the plurality of imaging devices 106.
Upon completion of the series of instructions, the computer system 104 will have a single or a plurality of images of the collectible 116, wherein each image is a high resolution image of at least a portion of the entire surface of the collectible 116 illuminated in a different lighting condition. Each image is labeled by the computer system 104 to identify the lighting condition it was taken. The images can be stored on an internal storage device of the computer system 104 or can be stored on an external storage device that is accessible by the computer system 104. The images will then be processed and analyzed under one or more image processing routines. In one aspect, after the computer system 104 receives the images from the image acquisition device 102, or from an image source external to the image acquisition device, the computer system 104 applies at least one image processing routine wherein the images are substantially aligned such that all the images are in substantially the same orientation and/or dimensions as each image in the database and with each future image created for grading. This allows for images to be overlaid and assist in the image processing. In some aspects, the system 100 comprises one or more collectible image sources and creates and stores one or more images of the respective collectible 116, wherein multiple collectibles 116 can be graded concurrently from each image source. For example, the system 100 can comprise a plurality of image acquisition devices 102 and/or configured to receive at least one external signal comprising an image of a collectible. This allows the system 100 to grade multiple collectibles 116 and operate in an efficient manner.
For a firmware and/or software implementation, the methodologies may be implemented with modules (e.g., procedures, functions, routines and so on) that perform the functions described herein. A machine-readable medium tangibly embodying instructions may be used in implementing the methodologies described herein. For example, software codes may be stored in a memory and executed by a processor unit. Memory may be implemented within the processor unit or external to the processor unit. As used herein, the term “memory” refers to types of long term, short term, volatile, nonvolatile, or other memory and is not to be limited to a particular type of memory or number of memories, or type of media upon which memory is stored.
If implemented in firmware and/or software, the functions may be stored as one or more instructions or code on a computer-readable medium. Examples include computer-readable media encoded with a data structure and computer-readable media encoded with a computer program. Computer-readable media includes physical computer storage media. A storage medium may be an available medium that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, solid state or other magnetic storage devices, or other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer; disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
In addition to storage on computer readable medium, instructions and/or data may be provided as signals on transmission media included in a communication apparatus. For example, a communication apparatus may include a transceiver having signals indicative of instructions and data. The instructions and data are configured to cause one or more processors to implement the functions outlined in the claims.
In one aspect, the computerized system 100 is configured to objectively grade collectibles 116, such as but not limited to baseball cards, according to a set of technical grading criteria (see listing of Table 1). The methodology for detecting defects in a collectible 116 comprises the collectible 116 being examined for variations of each criteria with respect to a perfect reference image or Golden Image stored in a database 130.
A Golden image 117 for a collectible 116, i.e., perfect image without any unintended defects included by its originator, may be created in the following manners: (1) An image of the collectible 116 in its original format (“Original Golden Image”) is supplied by its creator and entered into the computerized system 100 and stored in a file (the “Image Library”) in a tangible computer memory medium, such as the database 130; (2) a Golden Image is created by altering and enhancing a collectible 116 image (“Virtual Golden Image”) by removing all detectable defects unintended by its originator through the use of image processing and storing the newly created Virtual Golden image in a “Golden Image Library” in a tangible computer memory medium, for example, in a data structure, such as the database 130; (3) the highest graded card graded by the system 100 becomes the de facto Golden image until a higher graded card is found; or (4) by using machine learning, assembling perfect portions of other copies of the same card contained within the database. In aspects where the golden image for a collectible is not available, the system can use the highest graded card as the defacto golden image. Subsequent grading of similar cards with higher grades can become the new golden image. The system 100 might not know what defects were unintended or get an original image from the creator to have a golden image. As such the system 100 is configured to create a golden image by using the highest graded card and/or with use of machine learning. In other aspects, the system 100 can create a golden image by taking portions of different graded cards that are highly graded and combine them with other high graded portions to form a golden image.
Machine learning maps visual features to an overall card grade that is accurate and consistent beyond what human graders can provide. In one aspect, a machine-learning algorithm, known as k-nearest neighbors, combines the values of measured attributes into a single score for the portion of the card or collectible being evaluated. In one aspect, the k value for the nearest neighbors can be 11, such that the eleven nearest neighbors are used. However, other k values for the nearest neighbor can be used and the disclosure is not intended to be limited to a value of 11 for k, where the value of k may differ for various defects. In an example of obtaining a corner score for a card using machine learning, the corner algorithm can examine a number of attributes, such as, for example, 4 attributes, and derive individual corner scores for each of the four corners. From those four individual corner scores, the overall card corner score is computed. The fundamental computation of a single corner score is derived from individual corner scores for each of the four corners using proprietary algorithms by weighting or relative values of each of the four corner scores to arrive at the single corner score. A weighting of the four corner scores may include a small increase in the minimum value in certain situations, such as, when the lowest scored corner is significantly different from the other three corners, or when the overall card grade will not be above a pre-established threshold grade (on a 10 and/or 1,000 point scale). The increase can be 0.25 point, but can be set at other values. The result is the overall card corner score that can be expressed on a 1000 point scale (that is, with a resolution of 1/1000). The card corner score can also be expressed with the same relative resolution on a 10 point scale. The machine learning algorithms can be further refined by input from trained professional human graders and/or machine learning.
The database 130 comprises a datastore of known collectibles, such as but not limited to baseball cards. The database 130 comprises as many images of collectible as possible, and grows as additional images are added. The database 130 can also grow as the computerized system 100 is used to grade collectibles. Along with each image, a set of metadata is stored, which can comprise information about the collectible or baseball card 116, such as but not limited to: manufacturer of the card; year of the card's manufacturing; series name of the card; name of player or person on the card; the card number; any variation particular to that card series, e.g. red-black or gray-black; any ownership and/or historical provenance information available; any distinctive features or other information unique to that particular card, e.g., distinctions such as, but not limited to, Hall of Fame, Rookie, traded, high number, limited production, etc.; geometric information about where the inner-image appears within the cardstock or value-altering variations, e.g., autographs on the card. This set of metadata is described in relation to baseball cards, but the metadata is not intended to be limited to baseball cards. Metadata of other types of collectibles can also be collected. The computerized system 100 can be configured to allow the addition of any grading-specific information into the computer system 104 in order to facilitate faster processing or specific tasks. For instance, the computer system 104 could receive a test file comprising a set of initial perceptual hashes, which would speed the matching of a newly-imaged collectible or card 116 to the known cards of the database 130. Alternatively, it might include information about the owner of the currently-imaged card or collectible 116, wherein the database 130 options can then be filtered by that information and the best-match of only that owner could be found.
In one aspect, a comparison between the image of the collectible 116 and the Golden image 117 is conducted by the computer system 104. The image of the collectible 116 is first obtained and identified, as discussed above, by the computer system 104, and the Golden image 117 corresponding to the collectible 116 is retrieved from the Golden Image Library stored on the database 130. After the Golden image 117 for the collectible 116 is retrieved, one or more image processing routines are applied to the image of the collectible 116 for the purpose of gathering all data applicable to making a determination of the authenticity, condition and grading of the collectible 116. An example of an image processing routine utilized is a card identification algorithm. The card-ID algorithm takes as input the image of the collectible or card 116 and outputs the identity of the card, if there is a match available in the database 130. If there is no match, the algorithm issues alert to indicate that this is the first time this specific collectible or card 116 has been seen and a prior image does not yet exist in the image database. In this case, information about the card (manufacturer, etc.) can be manually inputted into the database 130, and that information along with the image of the collectible or card 116 will be added to the database 130, available for future collectible identifications. The card-ID algorithm distills all of the captured images of the collectible or card 116 into the database 130 in 64-bit perceptual hashes, as known in the art.
When the system 104 receives a newly-obtained image of a collectible or card 116, its 64-bit perceptual hash is also computed. Then, the perceptual hash of the newly-obtained image is compared to all of the known hashes from the database 130. The top 200 closest matches are then considered, one-by-one, and the collectible's or card's 116 pixels are directly compared to the images in the database 130 using a template matching process, such as but not limited to OpenCV's template-matching. The best of those template-matched images, if within a threshold, is declared the correct match or archived, if running in batch mode. If none of the images matches within the threshold, the system 104 declares that no match was found. The system 104 is not intended to be limited to computing 64-bit perceptual hashes of the images. In some aspects, the system 104 can compute perceptual hashes of varying sizes, higher or lower than 64-bit, such as but not limited to, 128-bit, 256-bit, etc. In some aspects, the system 104 can utilize various hash functions and is not intended to be limited to perceptual hash functions.
Table 1 identifies various specific criteria that may be examined by the image processing methods of the disclosure, in any combination, using six broad categories of criteria. Through the use of thresholds and algorithms, collectible 116 data is collected and applied to four condensed categories (Front and Back): (1) Corners; (2) Edges; (3) Surface; and (4) Centering. Within each category, as well as for general eye appeal, many image processing methods/algorithms may be utilized so that, for example, 72 or more criteria may be evaluated and analyzed for each collectible 116.
After all the images are collected and processed, 50 separate raw data scores of 1-1,000 are determined for each card—25 for the front side and 25 for the back side, thereby giving a total maximum raw card score of 50,000. The raw scores can be collected for the front and back as follows: 16 raw corner scores comprised of scores up to a maximum of 1,000 each for Fray, Fill, Residual and Angle (these terms to be defined within), thereby a maximum “Raw” score of 4,000 for each of the four corners for a total of 16,000 for corners; 4 Centering (defined herein) scores up to a maximum of 1,000 each for—top, bottom, left, right, thereby a maximum total raw score of 4,000 for centering; 4 Edge (defined herein) scores—up to a maximum raw score of 1,000 each for top, bottom, left, right thereby a maximum total raw Edge score of 4,000 for edges; 1 Surface score (defined herein)—combining the data from all surface defects for maximum raw Surface score of 1,000 for surface. This provides a possible maximum total raw score of 25,000 each for front and back of the card.
The 25 raw scores for front and back are processed by proprietary algorithms to arrive at 11 attribute scores, for each of the front and back of the collectible, up to a maximum of 1,000 each for front and back: 4 attribute Corner Scores up to a maximum attribute score of 4,000; 2 attribute Centering Scores, for top/bottom and left/right, up to a maximum attribute score of 2,000; 4 attribute Edge Scores, for top, bottom, left and right, up to a maximum attribute score of 4,000; and 1 attribute Surface Score up to a maximum attribute score of 1,000. This then provides a possible maximum total attribute score of 11,000 each for front and back of the card for a total of 22,000. These scores are then processed by proprietary algorithms to arrive at a single Card Grade with a maximum possible Card Grade of 1000. The numeric values used herein are illustrative but do not limit this disclosure in any way. This disclosure's algorithms can use scales sufficient to capture the accuracy and repeatability or reproducibility of the image-processing and final grades.
The computerized system 100 can utilize numerous image processing tools. The underlying image processing technology required for carrying out the various aspects of the disclosure and variations thereof is readily available in the art. For example, facial recognition technology utilizes a “Subject” photo and scans one or more databases (Image Libraries) to locate the Subject within the Library. In this locator process the purpose is to identify the Subject and to compare the Subject to a Golden Image once retrieved from an image library for the purpose of establishing a probability of a “match”.
In some aspects, the system 100 may be configured to identify one or more regions of the collectible, where the one or more regions comprise a portion of the collectible. The one or more identified regions may be prioritized based on an identifiable content of the collectible within the portion of the collectible. A first region of the one or more regions may comprise facial features of the collectible. The first region may be prioritized for grading. In such instances, a box or other indicator may be generated around the first region. The one or more identified regions may be viewable on the output device 122. The system 100 may identify multiple types of regions, which may include facial regions and specify regions of the collectible surface identifiable as higher-value to the grading algorithms. In some aspects, for example for facial regions, the system may utilize facial recognition technology for the purposes of identifying the one or more regions containing player faces, even when such faces are at different angles, or if partially obscured, such as beneath a goalie or catcher masks. The system may be capable of differentiating between the players referenced in the collectible image in comparison to ancillary facial imagery that may typically exist in the background. The system also implements the identification and classification of “higher-value” regions of the collectible, where observed defects in such areas are more heavily weighted with deductions. All such regions are identified to the end-consumer as regional bounding/bordered box areas, visible in the detailed grading report.
In some aspects, the system 100 may be configured to assign a deduction to each defect identified on the collectible. The deduction may be used to score the identified defects. The grade report of the collectible may comprise one or more deductions for one or more defects. The deduction may be applied to each defect identified on a front surface of the collectible, to each defect identified on a back surface of the collectible, or to any defect identified on any surface of the collectible. The system 100 may implement a set of models to establish a translation of observed defects of all types to a measurement-specific deduction (e.g., corner fill, corner fray, edge fill, edge fray, corner surface wear, edge surface wear, surface defects of all types, corner angle, size, etc.) and to the relationship between these individual measurements, to derive a final score. For example, an example of a hierarchy may depict how individual measurement defects are effectively “rolled up” into a final score:
Final Score
The models that determine how the above measurements are rolled up into the final scoring may be based on measurement-specific ratio scales or non-linear equations to determine bonuses or further deductions from a lowest score within the relevant comparison. Every rollup may begin with the lowest derived score for that specific measurement, and then all other related scores, based on their ranged distribution from the lowest score, may be used to determine potential increases (e.g., bonus) or decreases (e.g., deductions) from the lowest score. As the total sample basis of all graded collectibles grows, the system 100 may utilize machine-learning to profile such measurement scores, bonuses, deductions, and/or rollups to ensure consistency and accuracy.
In one aspect, the computerized system 100 measures light diffraction from an edge or surface defect and measures peaks and valleys on the edge indicating extrusions or indents on the edge relative to a straight line fitted on the edge or as with surface defects with high precision measurement of the degree (length, width, depth, and overall area) of light diffusion by number of pixels or other area measurement. Mixing Red, Green and Blue to form millions of colors and shades of similar colors creates the color palette from which all colors are derived. The computerized system 100 may, for example, utilize 256 different reds, 256 different blues and 256 different greens (the known color palate) to create the entire color palette of 16,777,216 different colors. With the use of highly sensitive lenses and resolution, individual pixels can be measured and any change in color, including color alteration, can be identified and measured. Any scratch or blemish may be identified and measured for length, width, depth, and overall area (in pixels for example) and location on the collectible 116. Light may be directed at the collectible 116 from above and the computerized system 100 identifies and measures the increase or decrease in the surface of the collectible 116 thus identifying depression in surface, pressing of materials, a wave on the surface, and/or altering of the paper stock within the collectible 116, etc.
In some aspects, the system may be configured to examine one or more edges of the collectible to determine whether at least one of the one or more edges is inconsistent with other edges. The determination of an inconsistent edge may be based at least on the at least one processing routine that detects variations or inconsistencies on one or more edges. In some instances, different type cutters may be identified as used on the collectible which may be based on different measured edge surface fraying (e.g., one of two or more types of detection of edge alteration methods). In an effort to improve the condition of a collectible, including trading cards, a card may be subjected to the removal of card stock (e.g., trimming). By trimming a card, it may result in a re-centering of the image on the card stock or, eliminating defects to one, or more, corners or edges of the collectible. The system may be configured to capture and evaluate for differences in a card's edges to determine if any of the card edges (and which one(s) have been trimmed by a cutting device. The system may be configured to detect and record the presence of micron-level variations in the object corner and edge areas based on the at least one processing routines described herein to the extent that variation from expected/standard occurrences of such observations may be used to identify statistically unlikely variations across object edges, effectively identifying cases where trimming has occurred.
Another example of an image processing routine is an image subtraction, wherein all data points on a Golden Image 117 may be utilized to eliminate all identical data points on the front and back of the collectible 116. The data that remains on the front or back of the collectible is thereby determined to be one or more defects (a mark or space not on the Golden Image) in the collectible. Image Subtraction may be utilized to determine differences in the collectible from the Golden Image such as but not limited to color (fading, alteration, re-coloring and other alterations; like bleaching of image and/or card, etc.) or scratches, chips, or dents. In similar fashion, image subtraction can also identify existing stains, added color to fill in areas of defect, printing errors, the effects of bleaching, stain removal, the addition of material (i.e., paper stock) or other material and image removal for the purpose of altering the width of the collectible's borders in an attempt to re-center the collectible.
The system 100 can be configured to calculate through the use of various pixel measurements at high magnification and resolution whether a collectible 116 has been resubmitted for grading by the system 100, and has either been switched or altered from its initial grading. Any previously graded card can be re-graded and can subsequently be authenticated as the original collectible thus eliminating counterfeiting and alteration. The system 100 may be configured to “fingerprint” each collectible using high-resolution imagery. The images captured by the image acquisition device 102 under the different lighting conditions highlight and uncover the unique physical characteristics and/or defects of each card that is graded by the system 100. These characteristics and/or defects are unique to each card and are difficult, if not impossible, to replicate. These images are stored on the database 103 and serve as a fingerprint of the graded card based on the physical characteristics and/or defects of the card. The system 100 may store the high-resolution image in a collectible image file and is able to use the “fingerprint” to authenticate a collectible that is in a holder (“Slab”) or other grading company's holder if the collectible was put in a slab by another company but graded by the system 100. In both instances, the collectible need not be removed from the holder (“Slab”) to authenticate it. The system 100 is able to store a high-resolution image of a collectible and create a “fingerprint” of the collectible for future authentication purposes of all collectibles graded by the system 100 even if the previously graded collectible remains in its slab. If a person desires, and if the image can be collected under acceptable lighting conditions, it may be possible to use a smart phone camera or other remote digital camera or smart phone app or other computerized application to record an image of the collectible for which authentication is desired. The system 100 may be configured to receive a signal external from the image acquisition device 102 comprising at least one image of the collectible to be authenticated and will identify its stored “fingerprint” image and compare the corners, borders, centering and edges for fiber, pixel and other measurement data that will confirm, at least preliminarily, if the collectible is the authentic collectible or a replacement (substitution) of a previously graded collectible or is a counterfeit of the collectible.
A corner algorithm measures several visual attributes whose combination will yield an accurate estimate of the corner score for each of the card's four corners. The source code serves as the most detailed definition of the image attributes, but we describe here the motivating idea for each:
Through the disclosure's proprietary algorithms, those four individual corner attribute scores are then calculated to generate a score for each of the corners and for the four corners as a single corner score of the subject card.
An edge algorithm measures at least three attributes for each of the four edges of the card from a certain distance from the corners, such as 0.75 inches from the corner. This distance can be adjusted by the system 104. Each of these three attributes corresponds may be used to identify defects on each of the four edges:
As with corners, the individual edge-score results from a learned relationship among these three attributes, based on knowledge from previously graded cards, predetermined perfect 90 degree angles or perfect straight lines, and/or from accepted and quantified industry standards. Through the disclosure's proprietary algorithms those four individual-edge scores, top, bottom, left and right, are then calculated to generate a score for the edges of the object card.
The outermost vertical and horizontal edges of a card when looked at, from above, at high resolution can show an imperfect edge that may have been subject to various points of indentation and/or expansion (peaks and valleys). These edge imperfections may be the result of improper or different cutting processes (e.g., roller or guillotine cut) of the edge, alterations of the edge, pressure from rubber bands, pressure from fingers, pressure from storage methodology or a card being impacted or dropped. Under high magnification and resolution they are unique and constitute a “fingerprint” for the card. The system 100 may be configured to fit a virtual line parallel to the outermost right and left side edges from the top edge of the card to the bottom edge of the card (“Vertical Centering Line” left or right, front or back) or from the left outermost edge of the card to the right outermost edge (“Horizontal Centering Line” top or bottom, front or back). Horizontal Centering Lines and Vertical Centering Lines run parallel to the outermost edge at the precise location determined by a threshold creating a virtual line to be fit through any imperfection, jag, hanging fibers, peaks (expansion), valleys (indents) to meet predetermined thresholds. Thresholds are fixed/preselected in an algorithm and establish what portion of an edge is defined as Peaks and what portion is defined as valleys (troughs). In one aspect, the system 100 may use up to five hundred measurement points along each edge to measure the Peaks and valleys to determine the number of each, their location, the area of each and the area of the surface of the card that is affected. Additionally, the system 100 may be configured to determine if the card outside edge has been cut or altered. The cut or altered edge has a different appearance than that of the other edges or of cards from the same series and/or set when compared to the “Golden Image.” The high-resolution image would be able to display the inconsistent appearance of the cut or altered edge. This high-resolution image of the peaks and valleys of the edges contribute (with other unique identifiers) to a “fingerprint” of the card that may be retained in the card Image File.
Image(s) and/or text are typically printed on the front and back surface of a card or collectible 116. The Vertical and Horizontal edges of the image and/or text on the front and/or back (left, right, top and bottom) of a card when looked at from directly above at high resolution will show an imperfect edge of the image and/or text as a result of print error or any aberrations (wandering pixel(s) that stray from the image during the printing process). The system 100 may be configured to establish the vertical and horizontal edge of the image and/or text of a card by fitting a virtual line along the edge of the image and/or text (looking down at the surface of the Subject) from the top of the card to the bottom (vertical image edge) or from the left edge of the image and/or text to the right edge of the image and/or text (horizontal image edge) defined by a threshold permitting that virtual line to be fit through an array of pixels, to meet a predetermined threshold. This process of fitting a virtual line may be identical to the process of fitting a virtual line on the outermost edge for Vertical and Horizontal centering Line.
On occasion, an image may extend to the outermost edge of the card. When this occurs, the Horizontal and Vertical centering Edges may be established at the outermost edge only. Centering is then measured by identifying a specific point on the Golden Image, or an image created by the system is used other than the Golden Image, that is in the precise center (“Centering Point”) of the Golden Image or the image created by the system. That Centering Point is isolated in pixels and placed on the Subject. The system 100 may be configured to utilize high resolution imaging to determine if the Centering Point from the Golden Image or the image created by the system is higher or lower (centering top and bottom) and left or right (centering left and right) on the card. This provides the system 100 the necessary data to calculate in Microns or Pixels or other increment what percentage the card image is off-center in any direction and/or that the card may be a possible altered or counterfeit card, as well as a contributor to a fingerprint identification.
When the outermost edge provides a border to the card, image pixel measurement or other image processing methods may be employed to measure the distance between the outer edge of the card and the outer edge of the image, both vertically (“Vertical Centering Lines”) and horizontally (“Horizontal Centering Lines”), front and back, as a means of establishing the width of all borders surrounding the image and/or text and thereby measuring the centering of the image and/or text on the Subject, front and back.
Pixel measurement or other image processing methods when used to measure the distance between the outer edge and the peaks and valleys of the card, create an absolute and unique “fingerprint” for that card, thereby permitting the system 100 to guarantee that if a previously graded card is re-examined by the system 100 for authentication, such authentication can be guaranteed and confirmed, or the card may be rejected by the system as a previously graded card thereby eliminating the resubmission of collectibles by anyone seeking to “grade shop” by resubmitting collectibles for grading in an attempt to get a higher grade.
The edges can also be measured using a binary large objects (“blob”) analysis, as shown in
In one aspect, the computer system 104 utilizes blob analysis in combination with various lighting configurations from above and below and high angle and low angle lighting precisely located relative to the surface of the Subject. Blob analysis, when used as a stand-alone tool measures light diffusion on the edge of a collectible 116, or on the surface of a collectible 116, which will identify and assist in measuring otherwise imperceptible cracks, creases, dents, fraying, chips and scratches. Light sources 114, for example LED lighting, will illuminate the defects that are typically undetectable by other means. Blob analysis may gather data relating to this light diffusion to quantify and measure the area in which the diffusion occurs. Blob analysis may then utilize pre-determined thresholds so that the light diffusion may be identified and measured for authentication and grading purposes. Blob analysis identifies defects in such high resolution that many defects while noted are too small or inconsequential to be of grading value. Predetermined thresholds may be utilized to determine which collectible 116 data collected by blob analysis will be used to later authenticate the collectible 116 (“Fingerprint”) for which purpose no defect is too small or inconsequential. These same thresholds may be utilized to determine which defects and data will be used to grade the collectible 116. When the data for grading purposes is determined, they can then be applied to create a collectible grade. If any blob analysis defects are below a size considered in grading and therefore not utilized in the collectible grading scheme, they may nevertheless be stored in the database 130 associated with the collectible image file and, for example, remain available for identification and authentication purposes (“fingerprint”) in the future.
Blob analysis may be combined with other image processing tools to identify defects on a collectible or card 116. In the card of
As shown in
A centering algorithm, as shown in
An industry-standard mapping of centering-ratios to overall centering-score is then used to find the overall centering-score for the card. For example, horizontal centering lines and horizontal centering edge are determined, and the system 104 can, for example, use up to 100 measurement points along the lines measuring the distance between the lines and resultantly any image slope (slant in the printing of the image on the card) associated with the image on the card. This calculation may be performed on Horizontal Centering Lines and Vertical Centering Lines to determine the width of the border on all sides of the image of the collectible 116. The system 104 calculation identifies the degree of off-centeredness of the image of the collectible 116 as well as the pixel variance on each border between the largest width and the narrowest width and compares them to the Golden image 117 to confirm they are defects. Thresholds may be applied and grading defects thereby determined. Defects outside the grading thresholds may be stored in the image file in the database 130 for authentication purposes, if needed, at a later date.
A surface algorithm seeks to give each object card a score based on the condition of the central surface of the card. Specifically, it downgrades this score based on, among other defects such as slope, the following card conditions:
In order to detect the many different types of surface defects, the system 104 compares the images taken under several distinct lighting conditions. These different lighting conditions accentuate the physical condition in the collectible 116 in order to detect the many different types of defects that could be present in a collectible. The computer system 104 compares the images taken under the different lighting conditions, and since the collectible 116 was stationary while the images were taken resulting in substantially aligned images, alignment of features from one image to another is made much easier: template-matching can align the images' features within one pixel—and, many times, to a precision greater than that. Even with no external template (that is, a database image) the difference in images between those lit from one side of the card and the other will reveal creases and other subtractive defects (pinholes).
In order to detect defects, the card needs to be compared to a template image, or in the absence of a template, portions of the card can be compared directly to other areas from the same image or a similar image, e.g., a different card from the same series. Each of the defects found, if any, would reduce the overall surface score for the card through algorithms consistent with standard card-grading practice.
The system 100 can be configured to employ Optical character recognition (“OCR”) to read the image and/or text on a collectible 116, and convert it into identifiable and readable text. Thus, the system 100 may use OCR or readable text to identify the collectible 116 in order to automatically locate its Golden Image 117, or the image created by the system other than the Golden Image, in the Golden Image Library or elsewhere in stored images (i.e., Subject Image File). The converted text can also be used to compile any other text data on a collectible (e.g. team, town, statistics, date, number, manufacturer, country, names, locations, etc.).
The system 100 may alternatively or also be configured to provide for Manual Input of a collectible 116 identifying data should it be a unique collectible or be otherwise unknown within the database 130. The system 100 may alternatively, or in addition, be configured to use Image Recognition technology known in the art to identify or match the collectible 116 with its corresponding Golden Image 117 file.
The system 100 may be configured to analyze the coloring of the collectible or card 116 and compare it to the Golden Image 117, or the image created by the system other than the Golden Image, using RGB (red, green blue) values for its color data. The red, green and blue coloration of each subject image may be evaluated and described as an average value for each color or for all the colors combined. The color data for each color of a collectible is then compared to the Golden Image, or the image created by the system other than the Golden Image, color data to determine how much the colors of the collectible vary from the colors of the Golden Image, or the image created by the system other than the Golden Image. The result is displayed as the “Color Difference” which represents an average difference of the red, green, and blue values and may be stored in computer-accessible computer memory or the database 130.
The system 100 may be configured to accurately measure the thickness of a card or collectible 116, for example, with a sensitivity of 0.25 microns, for the purpose of determining: if the card is counterfeit and on paper stock dissimilar from the Golden image 117, or the image created by the system other than the Golden Image; if the card has been “pressed” in an attempt to remove a surface crease; if the card has had one or more corners pressed in an attempt to “press” lifting of corner stock; and, if the card is a previously graded card by the system 104. For Example, this measurement may be performed using a Confocal Fiber Displacement Sensor which uses LED lighting (with which the imaging device 106 is equipped), without contact with the card, to more precisely measure the thickness than previously available technology such as laser triangulation. Thickness measurement may also be performed by other non-contact methods known in the art, such as terahertz time-domain spectroscopy (see Mousavi et al, Simultaneous composition and thickness measurement of paper using terahertz time-domain spectroscopy, Applied Optics, Vol. 48, Issue 33, pp. 6541-6546 (2009)) and multiwavelength THz interferometry (see Nguyen et al., Optical thickness measurement with multiwavelength THz interferometry, Optics and Lasers in Engineering, Volume 61, October 2014, Pages 19-22).
The above sections describe how the system arrives at an object-card score for each of four large grading criteria: Centering, Corners, Edge, and Surface (including color and gloss). From those four scores, measured on a 0-1000 scale, say, a single overall score for the card is computed based on the weighting determined by proprietary algorithms and that is standard in the card-grading industry. Because the usual output is provided on a scale from 0 to 10, the system can scale its overall score to that range or any other range selected. For example, the scoring may be scaled to correlate to a score or scale based on the range of 1-10 grade value. In some aspects, the grade report may comprise one or more different scoring metrics.
In order to display its processing results to an output device 122, the system 104 generates a grade report which may comprise a Detailed Image and Grading Report, for example in HTML, creating each score (and all of their component attributes) as quickly as possible, and swapping the actual results for their placeholders as they become available. The use of Javascript and its many libraries, e.g., AJAX, makes that swapping possible. By the end of the analysis, the user has access to all of the attributes, scores, raw scores, and overall score from the system. In addition, the images of the card and grade report for the card is added to the database 130 in order to improve future reasoning about identity or quality of scanned or camera-produced images. In addition, storing the card images in the database 130 enables the system 104 to identify individual instances of cards, for authentication and to facilitate alteration detection and/or counterfeit detection.
With individual instances of scanned cards or collectibles 116 available in the database 130, the system 104 can use the same techniques described above to solve—or facilitate—authentication of three types:
The system 104 can comprise a graphical user interface on the output device 122 that allows a user, through customary mouse motions and other input gestures, to specify the locations in a card where the system would check for known discrepancies that would signal a possible counterfeit.
The computerized system 100 creates an image file of the collectible 116 and this file may be stored in the database 130 in remote network-linked computer memory devices, and remain accessible to the computerized system 100 and its customers. The collectible 116 image in the database 130 is also a “Detail Fingerprint” of the collectible 116. In the images stored at the resolution used by the system 100, the corners and centering are unique and cannot ever be reproduced or counterfeited. The computerized system 100 can measure and capture an image of a corner and/or the centering (width of image borders horizontal and vertical) in such detail that the corner and centering of the image on the collectible or card 116 could always be confirmed in the future. The computerized system 100 measures the edge of each collectible 116 precisely such that the system 100 is able to identify “peaks” and “valleys” on each edge. These peaks and valleys are unique and can never be reproduced or counterfeited. By retaining a high resolution image of the graded collectible 116 (“Detail Fingerprint”) a person at any time in the future can send the collectible 116, or its image via any electronic means, to be authenticated by the system 100 and confirm that the collectible 116 is the same collectible 116 as originally analyzed and graded. A person may also confirm that the collectible 116 of inquiry is not a counterfeit of the original collectible 116.
At least one advantage of the disclosure is that a graded card or collectible 116 can be authenticated, while the card is either within or removed from its original grading holder, at any time after the initial grading. This provides the added security to ensure that the card being authenticated or regraded is the identical card that was originally graded by the disclosure. The disclosure provides a higher security measure over conventional grading companies, which typically issue a serial number to the card they grade, and/or a certification that the card was graded by them. Conventional grading companies retain a database of the serial numbers for the cards they have graded, but do not retain a “Detail Fingerprint” of the graded card detailing the physical condition of the card and/or defects at the time the card was graded (a card “Detail Fingerprint”). Cards graded under conventional processes can be resubmitted until a desired high grade is obtained. The high grade is obtained due to different humans examining the card or manual graders seeing the card defects differently. This variance in how a card is seen may be referred to as human eyesight error factor. The disclosure will identify that a card has been graded and provide a grade that is identical or consistent with the original grade. The subsequent grade could be lower than the original grade if the condition of the card has changed since it was originally graded. As such, the disclosure prevents the inflation of grades of cards and thusly eliminates the reason cards are resubmitted for grading, when the card is manually graded.
Yet another advantage of the disclosure is to further assist the marketplace in discerning whether a collectible 116 is counterfeit or has been replaced with another collectible (card “substitution”). For example, a card that is not a counterfeit, but is not the identical card that was originally graded. Generally, the substituted card is of a lesser condition and, therefore of lower value. The system 100 may maintain ownership data for each collectible 116 and this information may be stored in a correlated manner with the “fingerprint” image, for example in a data structure such as the database 130. In one aspect, a person may be granted access to the database 130 and confirm that the owner of the collectible 116 is as represented by a third party. This feature permits a buyer of a collectible 116 to confirm that the collectible 116 is authentic and that the seller is the legitimate owner. With each transfer of ownership, a recorded owner and a buyer together will have access to update the ownership record in the database 130.
In one aspect, the computerized system 100 uses a 1,000 point grading system and converts data collected by image processing to a numeric score and a standardized grade. For example, a 1,000 point max scale may be reduced by thresholds and applied algorithms such that the final score is 815. The 815 may be reported at its corresponding 1-10 point scale and with the applicable grade (i.e., Perfect, Pristine, Gem Mint, Mint, Mint/Near Mint, Near Mint/Excellent, Excellent/Good, Good/Fair/Poor, etc.). Unlike other grading companies, the computerized system 100 may be configured to provide a Detailed Image and Grading Report comprising a detailed defect report itemizing any and/or all deductions in score. The Detailed Image and Grading Report can also comprise a detailed image report that will show an image of the collectible 116 with the location of noted defects identified. The grade report may also be configured to provide a provenance report and authentication report in order to eliminate counterfeiting and fraud (alterations). This 1,000 point grading system also provides an opportunity for collectible 116 owners to differentiate their graded collectibles 116 by score and/or grade report. Thus permitting two collectibles 116 graded with the same standardized grade (Mint/Near Mint for example) to differentiate their collectibles 116 and more precisely determine relative value. Additionally, people who value certain type defects differently may differentiate between collectibles 116 both scored the same (815 and 815, for example) but with different defect attributes. For example, because general eye appeal may be an important component of value for a particular buyer and “beauty” is in the eye of the beholder, one collector may value good corners more than centering or gloss than another collector does and will be able to discern the grading details to exercise his/her preference.
In some aspects, to generate the Detailed Image and Grading Report, the system may be configured to identify at least one defect of the collectible by including at least one indicator on an image that comprises the at least one defect. The at least one indicator may comprise an indicator that indicates a defect location based on horizontal and vertical coordinates. The Detailed Image and Grading Report may comprise a detailed defect report of the at least one defect of the collectible. The Detailed Image and Grading Report may allow for the at least one defect of the collectible to be specified and viewable, for example on the output device 122. The at least one defect may be identified by the at least one indicator.
The computerized system can be configured to prepare various types of reports and is not intended to be limited to only producing grade reports. In some aspects the computerized system can be configured to prepare and/or produce a plurality of reports based on the information stored in the database 130.
In some aspects, the database 130 comprises a plurality of databases. For example, the database 130 may comprise a grade report database, wherein the grade report of the collectible is stored on the grade report database. Information related to the collectible may be stored on the grade report database. In some aspects, the information related to the collectible may comprise at least a geographical location of the graded collectible. The information related to the geographic location of the graded collectible may be available to indicate a location of the graded collectible.
In some aspects, the computerized system can be configured to prepare a population report of all the collectibles that have been graded by the computerized system. A population report can be derived from various data points and/or metrics stored in the database. In some aspects, the data points and/or metrics can comprise the year the collectible was created, manufacturer of the collectible, the main subject of the collectible (i.e. baseball player on the card or other player), number of the collectible from a series of collectibles, sport of the collectible, awards received by the main subject or player (i.e. Most Valuable Player, Rookie of the Year, etc.), individual statistical information (i.e. batting average, earned run average, etc.), and/or championships won. This list is a non-exhaustive example of possible data points and/or metrics that could be used to formulate the population report, and the disclosure is not intended to be limited to the non-exhaustive example disclosed herein. Persons skilled in the art would understand the vast variety of possible data points and/or metrics that could be used to formulate the population report.
In some aspects, the data points and/or metrics can comprise many different characteristics that are related to the collectible. In the non-exhaustive example provided herein, the types of data points and/or metrics listed of the collectible are those related to baseball cards, but the disclosure is not intended to be limited to baseball cards. The types of data points and/or metrics are not intended to be limited to baseball cards, and can be directed to many different types of collectibles, such as, but not limited to, football cards, basketball cards, hockey cards, stamps, coins, photographs, and/or any other type of collectibles.
In some aspects, the information related to the collectible may comprise a population report comprising at least one of a scarcity of graded collectibles, an amount of total graded collectibles, or an amount of total graded collectibles of a specific collectible. Collectibles graded by the grading apparatus may be identified by the submitter of the collectible to be graded. For example, personal identification characteristics which may also include geographical location of the graded collectible, as well as the grade of the graded collectible. In some aspects, this information may be publicly available in a searchable database enabling the public to see a graded card population by card, grade, location, etc. A population report by geographic location permits a collectible owner to know where pockets of similar cards are located and, if elected, go to trade shows in the geographic location to buy or sell collectibles in geographic locations where the collectible is more likely to sell or sell at a higher value due to a lack of availability of such collectibles in the geographic location.
In some aspects, the information related to the collectible may comprise at least an order grading. The order grading may be based at least on one of an order of grading by the grading apparatus, an order of grading of a specific collectible by the grading apparatus, a ranking of the collectible based on its grade as reflected on the collectible, or a grade population report indicating a number of same collectibles graded by the grading apparatus.
The report 1800 can also arrange the cards by grade, such that the results can be arranged to show the number of graded cards by range of grade. For example, as shown in
At least one advantage of the disclosure is that the population report 1800 provides an accurate count of cards by grade and will also eliminate cards that have been submitted for regrades. In conventional reports, when a card is re-submitted to be re-graded, which is very common in the industry, the prior grade is not replaced by the new re-grade value and is thus counted multiple times, such that conventional reports do not account for cards that have been submitted multiple times for grading. As such, conventional reports do not show an accurate count of the number of graded cards because cards re-submitted for re-grade are counted as new cards and there is no way to determine whether a card has previously been submitted for a grade.
As discussed above, the computerized system can determine if a card has been submitted previously for a grade, such that if a card is identified by the computerized system as a card that has been previously submitted for grading, then the previous grade will be replaced and/or updated with the new grade, or the card will be returned ungraded due to it being a resubmission. The system may not permit a card resubmitted for grading to receive a higher grade when resubmitted. The computerized system can also store the number of times a card has been re-submitted for grading. As such, the population report 1800 of the disclosure provides an accurate number of graded cards because the computerized system of the disclosure can detect and/or account for re-submitted cards. Conventional reports have inaccurate card counts because cards are repeatedly re-submitted for re-grading until the card has achieved the highest possible grading, which in turn leads to multiple grades for one card and gives the impression that there are more cards than what is actually present. Also, manual grading companies do not disclose on a resubmitted card that it has been previously graded and/or disclose the previous grade a resubmitted card received when initially graded
In some aspects of determining if a card has been previously graded by the computerized system, the computerized system will capture one or more images of the card, as would be done for any card during the grading process. The images are then transmitted by the image acquisition device, such as but not limited to a scanner, to a processor, wherein the processor will apply one or more image processing routines to the one or more images. As a result of the one or more image processing routines, defects and/or imperfections are identified on the card, and the computerized system can run a comparison analysis on results of previously graded cards that are stored on the database. If a previously graded card is found to have the substantially similar defect and/or imperfection, then the computerized system will mark the card being graded as a potential resubmitted card. In some aspects, the computerized system can further analyze the potential resubmitted card with the previous results to ensure that the card under examination has been previously graded. Such further analysis can comprise a comparison of physical condition of the cards, such as but not limited to quality of corners, physical dimensions, same picture on cards, centering of picture on card, and/or any other items disclosed above in Table 1. In the event that such a card is determined to be a resubmitted card, then the previous grade report of the resubmitted card is updated with the results of the re-grade, or the card is rejected for grading to avoid a resubmitted card receiving a higher grade than initially graded. If a resubmitted card is graded higher the second time graded, the disclosure may determine the card is altered. The grade report can also be updated to indicate that the card has been resubmitted for grading, as well as the number of times the card has been resubmitted for grading. This allows the computerized system to ensure an accurate accounting of the number of cards that have been graded by the computerized system. As discussed above, it is common for cards to be resubmitted for grades until the highest possible grade for a card is attained, but conventional grading systems do not account for a card being resubmitted for grading and thereby do not have an accurate record of the actual number of unique cards that have been submitted for grading. At least one advantage of the computerized system is that it can provide an accurate accounting of the number of graded cards, and can detect when cards are being resubmitted in an attempt to get a higher grade. This can instill confidence into the computerized grading process because the subjective human element is significantly reduced and/or eliminated, and making the grading process more objective and less susceptible to “grade shopping” and/or alteration.
In some aspects, the computerized system can determine if a resubmitted card has been altered from its physical condition from the previous time it was submitted for grading. For example, if the card when originally graded had rough edges and/or corners, but when resubmitted has straight edges and/or straight corners, then the computerized system will be able to analyze the card to see if the dimensions have changed to reflect that the card edges and/or corners were cut in an attempt to improve the edges and/or corners of the card. Such information will be included in the updated grade report. In another example, if the originally graded card had missing color along a portion of the card (due to frayed corners/edges, or other reason), but when resubmitted, the card does not have the same missing color, the computerized system can determine if the card was altered by adding coloring to the portion of the card. In yet some aspects, the computerized system examines the centering of the photo to determine if the centering of the photo has been altered since last submitted. The computerized system can perform a centering analysis, as discussed above, to determine the separation of the photo from the edges and if the separation has changed since last graded, then the computerized system can detect the change in centering, and can thereby determine that the card has been altered since it was previously graded. In yet some aspects, the corners are examined to determine whether the corners are in the same condition as before. In yet some aspects, the corner or edge fray are examined to determine whether the corners or edges are in the same condition as when originally created or if the corner or edges have been altered.
In the aspect of
The grade of Proof is for a card that is determined electronically to be “perfect” by definition with no identifiable defect above the scoring threshold. This determination is made without the card ever being touched by un-gloved human hands.
The grade of Near-Proof is for a card that is an otherwise Proof-graded card but touched by human hands.
As discussed above, the grading scale can range from 100-1000, and in some aspects, the grades of Proof and Near-Proof may be within the 100-1000 scale.
In some aspects, cards that have been graded as Proof or Near-Proof can be specially encased in a protective casing 1900, as shown in
The protective casing 1900 can comprise a central body 1910 that receives the slab 1902 with the collectible, a front cover 1912, a back cover 1914, and a spine 1916, wherein the front cover and/or the back cover are hingedly coupled to the spine 1916. The central body 1910 can be coupled to the spine 1916 such that the central body is affixed and stationary. The front cover and/or the back cover can further comprise a padded section 1918, such that the padded sections contact the central body 1910 when the front and back covers are closed, such that the padded sections and the front and back covers provide a protective cover to opposite surfaces of the central body 1910. The protective casing described is merely exemplary and may be designed and configured differently, and is not intended to be limited to the aspects disclosed herein. The Proof and Near Proof casing may contain internal lighting.
The protective casing shown in
In some aspects, the system for grading a collectible comprises an encasing apparatus configured to encase a graded collectible within a protective slab (e.g., 1902 of
A “flip” is commonly used in the industry to refer to the piece of paper on which all relevant card data that is inserted into the slabs prior to sealing (e.g., sonic welding). The system may utilize a flatbed UV printer with instantly curing UV ink to print collectible-relevant and scoring-relevant information on the slab. In some aspects, collectibles graded in a high range of 10 may receive a “pristine” categorization. The printer may use different layers to print information related to the collectible. For example, a number of layers may be printed in a variety of layer order, a first layer may be a security mark layer, a second layer may be a contrasting layer of another color. A third layer may be a background layer printed in another color. A fourth layer may be an identification layer comprising information related to the collectible and grading information of the collectible. In some aspects, the identification layer may comprise a QR code linked to the Detail Image and Grading Report. At least an advantage of the disclosure is that by printing on the slabs directly, the potential for substitution or fraud a scenario in which a person cracks open one slab, removes the paper flip, and places it in another slab with a lesser value card or replaces the flip with a facsimile indicating a higher grade, passing it off as the original may be eliminated. Since the score is UV printed directly on the slab, any cracking of the slab may also destroy the grading. Once cracked, a slab is unable to be re-sealed again without visible distress marks or frosting.
In some aspects, an imaging device (e.g., image acquisition device 102) may be configured to capture at least one image of the collectible within the protective slab. The at least one image of the collectible may be stored on a database. The at least one image of the collectible may be available, from the grading apparatus, for submission to an online platform for sale. After a collectible is graded and encased within the protective slab, one or more images may be captured of the collectible within the protective slab. The one or more images may be provided to the customer directly through an online platform or exchange, such as but not limited to an order management system (OMS). This allows for a standardization of all images of the grading system. The one or more images may be located within an order in the OMS, clickable and downloadable by the customer. All images may then be used to upload from the OMS directly to secondary marketplace platforms for resale purposes. This eliminates the time consuming process that the submitter must go through to submit cards for sale without the return of the cards and the re-shipping of the cards to the selected platform. This also eliminates the need for the submitter to take images of the graded card to post with the selling platform.
In some aspects, the grading apparatus is configured to generate a non-fungible token (NFT) of the collectible. For example, the NFT of the collectible may comprise the collectible at different stages of a grading process. Upon grading of a collectible, the condition of the submitted collectible is assessed. By doing so, the system may create a new asset for each customer where each NFT may become an additional collectible. The system may create one or more NFTs of the collectible during the grading process. The system may create an NFT out of each card itself. For example, a collectible graded with a score of 10 Pristine, may have an NFT created of the grading so that the customer has the opportunity to be the owner of the digital asset created upon grading of their physical asset. The system may provide the customer with an option to purchase or sell the NFT of their graded collectible. The system may also create an NFT of that same collectible graded as Pristine, or Proof or Near-Proof based on a recording of the grading process. In some aspects, the system may comprise a video recording system. The video recording system may record at least a portion of a grading process of the collectible. A recording of at least the portion of the grading process of the collectible may be available for sale to the party that submitted the collectible for grading or utilized for security purposes. In some aspects, the portion of grading process may include receipt of the collectible, an image acquisition of the collectible, printing information of the collectible onto the slab, encasing of the collectible within the protective slab, grading of the collectible, or shipment of the graded collectible. In some aspects, the recording of the portion of the grading process may be utilized for identifying the portion within the grading process, actual grading, authentication of the graded collectible, or security to identify a location of the collectible at a time an image or a part of the grading process of the collectible was last obtained. The recording of the grading process may be a continuous video of the entire grading process or a non-continuous video of the entire grading process.
In some aspects, a submission kit 2600 of
In some aspects, the system further includes a foil wrap mechanism. The foil wrap mechanism may be configured to wrap the entire graded collectible, graded by the grading apparatus, within the protective slab within a foil wrapping. The foil wrapping may comprise at least one of a tracking device, information related to the graded collectible, or a grading of the graded collectible. Foil Packs are most commonly seen in many retail stores wrapped in silver foil to give trading card packs not only a pristine look, but to fulfill the excitement one may receive when opening a pack of cards sometimes referred to as “ripping wax.” The system may allow customers to have the option to have each one of their graded cards foil wrapped. Often times collectors will want to video their experience of opening packs called “case breaking” or “box breaking” with the newest trading card box to hit the market. However, foil wrapping graded collectibles takes this one step further such that customers, retailers, podcasters social media personalities, etc., may be able to unwrap their graded collectible in one single reveal, or may unwarp their collectible in “one at a time” reveals of certain aspects of the slabbed card. For example, the reveal of the foil wrapped card may be a single subscore at a time for the four subscores printer on the slab. Then, after the individual subscore reveals, the final card grade may be revealed, either as a reveal of the TAG and industry card grade together or in a one at a time reveal. This foil wrap is intended to gamify the reveal of the TAG slab and/or grade details in a manner that emulate the excitement and entertainment of ripping wax (of i.e., opening a pack of trading cards).
The custom set registry (CSR) report 2100 can be displayed on the output device 122 or can be displayed on a remote output device that is connected to the computerized system, such as but not limited to a network connection, such that the customized set registry report 2100 can be accessed and/or displayed on an output device 122 that is remote from the computerized system. The customized set registry report 2100 can be shown on any output device, either remote or local to the computerized system, that has a graphic user interface that acts in response to instructions received by the computerized system. An output device may comprise any device including but not limited to computers, smartphones, tablets, or the like.
As discussed above, metadata is collected and/or attributed to collectibles or cards as they are being graded. Metadata that has been collected of a graded card can be utilized in creating the custom set registry report or reports from the population report that fit the filters that the system can create to provide existing collectors and/or “beginners” with suggestions of possible Custom Set Registries for which cards graded by the system already exist. Customers may submit their own combination of filters from the list of filters that may be retained in a database and request a report on the cards that are responsive to the selected filters. The system may be configured to offer for sale such lists to the marketplace. Metadata can refer to many different descriptive features of the card, player information, statistical information, manufacturer of the card, year of the card, number of card, name of series that the card is a part of, career statistics and/or awards, team statistics and/or awards, special characteristic of card (e.g., limited-edition card, first ever card, autograph, and/or special insert embedded within card, premium card, semi-premium card, or most common cards), or the like. The computerized system can gather and compile a vast array of metadata information for each player and store it, making it accessible to create Customized Set Registries, whereby a customer may create, using filters, a personalized list and/or collection of cards which meet their criteria. For example, one may wish to accumulate a collection of cards of Pitchers from 1957 to 1973 in the National League with more than 100 wins, more than 300 strikeouts, and an ERA of less than 3.00. The metadata can allow the computerized system to create an infinite variety of Custom Set Registry reports based on metadata and advanced sabermetrics to be registered enabling the customer to accumulate the desired collection. In some aspects, some of the selected metadata may be listed on the flip of a graded card.
Users may add to or reduce the customer selected filters for Custom Set Registry in real time with the Custom Set Registry report indicating with each change of filter the impact on number of cards that satisfy the filters currently selected. This real time customer option permits the customer to build their set to contain a preferred number of cards. The Custom Set Registry may also provide current market values for the cards selected such that the customer may change selected filters to fit within a specified estimated purchase price for the cards selected with the chosen filters. The customer may change the filters to increase or decrease the estimated amount of money the purchase of the Custom Set will require. Once a list of qualifying players is determined by the User to be satisfactory the list may be saved as a Custom Set Registry report. A Custom Set Registry report can be saved on the database 130 or on a separate storage device and can be configured to be accessed by the public or saved as a private report such that it cannot be openly accessed by the public. The Custom Set Registry report can create a set of cards that a user would like to collect which could allow a user to collect very scarce cards without their Custom Set Registry report creating attention and possibly more competition. The Custom Set can include a scarcity report drawn from the TAG Population database/Report indicating a difficulty level the desires Custom Set will be to complete. The Custom Set Registry can provide a point system to rate each Custom Set on factors that include, but are not limited to, scarcity, value, condition, etc. The Custom Set Registry report can be configured to provide the user the option to grade a card that they have obtained that is part of their Custom Set Registry report. The user can then notify the computerized system that such card from their set registry report will be submitted for grading, and upon the completion of the grading, such grade will be populated on their Custom Set Registry.
The Custom Set Registry report can identify cards that have been graded by the computerized system, and organize them by grade or any other selected criteria such as, but not limited to, player, manufacturer, year, position, etc. Additionally, cards that are part of the Custom Set Registry report can be cards that have not been graded by the computerized system. This allows the user to know which cards of the Custom Set Registry report have been graded by the computerized system and which have not. In some aspects, the Custom Set Registry report can be customized to only include cards that have been graded by the computerized system. In some aspects, the Custom Set Registry report can be customized to only include cards that have not been graded by the computerized system. In yet some aspects, the Custom Set Registry report can be customized to include cards that have or have not been graded by the computerized system. The customization of the Custom Set Registry report is determined by the user and can be set based on any of the criteria discussed herein.
A Custom Set Registry report user may elect to make their Custom Set Registry report public to gain assistance from and access to others in order to identify the possible availability and/or source of specific cards in the Custom Set Registry report. The Custom Set Registry report can be accessible through a network interface, such as but not limited to an internet website created by the computerized system or an external system that uploads the Custom Set Registry report to the database 130. The website will permit collectors to communicate with each other regarding customized set registries or Custom Set Registry reports, and the website will be at least one manner for the parties to communicate without their identities being disclosed. The set registry report user can post their cards that are part of their set registry report that have been graded by the computerized system. The user can allow only the grade to be visible to the public, or can allow the entire grade report to be visible to the public. A trading exchange may be created that comprises a searchable database of cards graded by the computerized system to allow users to purchase and/or sell a card within a public Set Registry which will be system-managed to protect the buyer (assures card purchased will be delivered) and seller (assured purchase price will be paid). In some aspects, the exchange may operate as a marketplace to offer the graded collectible for sale. In some aspects, the exchange may be limited to graded collectibles that have been graded by the grading apparatus. The exchange may also include non-graded collectibles.
In some aspects, the marketplace may offer graded collectibles, graded by the grading apparatus, with a put option including a right, as holder of the put option, to sell the graded collectible at a future time within a specified time and at a specified price. The put option may comprise an option to sell a specified collectible at a put option price, wherein an actual price of the specified collectible is less than the put option price. In some aspects, the marketplace may offer the graded collectibles, graded by the grading apparatus with a call option including a right, as holder of the call option to purchase the graded collectible at the future time within the specified time and at the specified price. The call option may comprise a contract between a buyer and a seller for the buyer to purchase a specified collectible until a defined expiration date. The call option may comprise a future call option, wherein the future call option is for a collectible not yet graded by the grading apparatus or of a collectible anticipated to be available in the future. For example, the future call option may be entered into for a collectible not yet in existence, such as but not limited to minor league players, college players, or the like, neither of which may have a specific collectible for which the option is purchased, as of the date the option is purchased. The future call option may identify the collectible by player name, manufacturer, and grading system grade. This feature permits a collector to contract to purchase a future rookie card for a player who has not yet become the subject of the manufacturer. The exchange that operates as the marketplace may be configured to offer the graded collectibles, graded by the grading apparatus, financing to purchasers of the graded collectibles or insurance to insure the purchaser of the graded collectibles that the collectible is graded by the apparatus or insurance against loss of the collectible graded by the apparatus.
In some aspects, the graded collectible may comprise a defect free collectible wherein the defect free collectible is graded directly from an unopened case, box, or pack of manufactured collectibles. In such aspects, the defect free collectible may be graded as a Proof collectible. The system may be configured to allow the Proof collectible to be offered for sale on the exchange. Proof cards only being sold on the exchange may allow for the authentication of the collectible as actually being a Proof graded collectible. A Proof collectible may comprise a collectible that is graded directly from an unopened case, box or pack of manufactured cards that remains unopened until graded by the grading apparatus. The system may grade the collectible by removing them from their original packaging without coming into contact with human hands. A collectible, in order to be graded as “Proof” must be determined by the grading system to be without defects. A “Proof” collectible once identified is catalogued by the grading system as Proof Identified, such that a second Proof collectible in not generated, thus assuring the market that each “Proof” collectible is one of a kind. Limiting the sale of the Proof collectible on the 3xchange will enable the market to know that each Proof collectible is as marketed as a one of a kind item.
At least one advantage of the disclosure is that the Custom Set Registry report can identify whether any cards that are part of the Custom Set Registry report have been graded by the computerized system. This will allow a collector to know whether any cards of the customized set or Custom Set Registry report have been graded which gives a higher degree of security and/or reliability of the number of graded cards available, since the computerized system can determine if a card has been re-submitted for a re-grade, as discussed above.
In some aspects, the system for grading the collectible may be comprised within a remote grading unit (“Pod”). Location data captured by the Order Management System may identify a physical location for the remote grading unit (Pod) based upon the geographic location from which cards are being submitted for grading. In some aspects, location data may be stored within a database to generate statistical data indicating usage of the apparatus. One or more steps of grading the collectible may be performed by the remote grading unit (Pod)eliminating the need for the card to be shipped to the apparatus that is located in the central office. For example, the remote grading unit (Pod) may be separate from a centralized system that performs one or more steps of the grading process. In some aspects, the remote grading unit may be configured to perform at least one of (1) an image acquisition of the collectible, (2) a verification of the collectible, (3) generation of the grade report, (4) printing of an encasement, or (4) the physical encasing of a graded collectible. The remote grading unit (Pod), in conjunction with a centralized grading unit, may be configured to grade the collectible. The remote grading unit or the centralized grading unit may perform one or more of (1) image acquisitions of the collectible, (2) the verification of the collectible, (3) the generation of the grade report, or (4) the physical encasing of the graded collectible. The system may enable the collectible grading technology to be placed within remote grading units (pods) in remote locations making grading of collectibles more easily available and at a reduced cost to the collectible owner. The remote Pods may indicate the submitted cards based on a zip code of the submitter submitting the card, or a location identifier assigned to each of the remote grading pods. Instead of having the collectibles sent to a centralized grading center, which may create the expense of shipping and insurance as well as resulting in longer grading times due to requirements for packaging and shipping times, the grading Pod may be located in geographic locations from where minimum thresholds of cards are sourced. In the collectible grading industry, premium charges (e.g., commonly $150 per card) may be charged for a faster turnaround time to get a graded card, however, the premium charge may still require the delay in grading times due to shipping and handling. At least one advantage of the grading pod is that the grading Pod minimizes a total cost for grading a collectible, and not only provides a faster turnaround time, which has been identified in the industry as one of the most significant issues but does so at a lower cost. Pods may be located in remote (remote to the central location) such as shopping centers, malls, retail stand-alone locations, and international locations. etc. The Pod is designed to avoid the submitter expense of shipping and the time of order submission and the risks that time represents to the value of cards due to player injury, etc. The Pod permits the grading technology to be done at the closest location to the submitter.
At 3502, the grading apparatus may receive at least one image of the collectible. For example, 3502 may be performed by processor 120 of the system 100. In some aspects, to receive the at least one image of the collectible, the collectible may be received by a slide actuator. The slide actuator transports the collectible in order for the apparatus to receive the at least one image of the collectible. In some aspects, to receive the at least one image of the collectible, the collectible may be received by the slide actuator that is positioned to receive an airflow blown over the collectible to remove airborne defects located between an image capture apparatus and a surface of the collectible. The airborne defects are removed and not captured by the image capture apparatus. In some aspects, to receive the at least one image of the collectible, the collectible is received by the slide actuator comprising a suction device to position the collectible under an image capture apparatus in a duplicable configuration, such that each of the at least one image is captured in a similar configuration. In some aspects, a control rate of at least one processing routine is based on a variable speed of a slide actuator. The slide actuator may comprise a loading tray to receive the collectible. The loading tray may be maneuvered by the slide actuator to position the collectible within the apparatus. In some aspects, to receive the at least one image of the collectible, the collectible may be received on a loading tray comprising one or more openings. The one or more openings may be covered by the collectible in response to the loading tray receiving the collectible.
At 3504, the grading apparatus may apply at least one processing routine to the at least one image. For example, 3504 may be performed by processor 120 of the system 100. The at least one processing routing may be applied in response to the grading apparatus receiving the at least one image of the collectible.
At 3506, the grading apparatus may generate a grade report of the collectible. For example, 3506 may be performed by processor 120 of the system 100. The grading apparatus may generate the grade report of the collectible based at least one results of the at least one processing routine. In some aspects, the apparatus for grading the collectible may be comprised within a remote grading unit. Location data captured at the remote grading unit may identify a physical location of the remote grading unit and the collectible submitted for grading. In some aspects, one or more steps of grading the collectible may be performed by the remote grading unit. In some aspects, location data may be stored within a database to generate statistical data indicating usage and an identity of collectibles submitted for grading. In some aspects, the remote grading unit may be configured to perform at least one of an image acquisition of the collectible, a verification of the collectible, generation of the grade report, printing of an encasement, or an encasing of a graded collectible. The remote grading unit in conjunction with a centralized grading unit may be configured to grade the collectible. The remote grading unit or the centralized grading unit may perform one or more of image acquisitions of the collectible, the verification of the collectible, the generation of the grade report, or the encasing of the graded collectible. In some aspects, the grade report may comprise a scoring within a range of 100 to 1000 point scoring. The scoring may be scaled to correlate to a collectible score based on a range of 1-10 grade value. The grade report comprises one or more different scoring metrics.
At 3602, the grading apparatus may receive at least one image of the collectible. For example, 3602 may be performed by processor 120 of the system 100. In some aspects, to receive the at least one image of the collectible, the collectible may be received by a slide actuator. The slide actuator transports the collectible in order for the apparatus to receive the at least one image of the collectible. In some aspects, to receive the at least one image of the collectible, the collectible may be received by the slide actuator that is positioned to receive an airflow blown over the collectible to remove airborne defects located between an image capture apparatus and a surface of the collectible. The airborne defects are removed and not captured by the image capture apparatus. In some aspects, to receive the at least one image of the collectible, the collectible is received by the slide actuator comprising a suction device to position the collectible under an image capture apparatus in a duplicable configuration, such that each of the at least one image is captured in a similar configuration. In some aspects, a control rate of at least one processing routine is based on a variable speed of a slide actuator. The slide actuator may comprise a loading tray to receive the collectible. The loading tray may be maneuvered by the slide actuator to position the collectible within the apparatus. In some aspects, to receive the at least one image of the collectible, the collectible may be received on a loading tray comprising one or more openings. The one or more openings may be covered by the collectible in response to the loading tray receiving the collectible.
At 3604, the grading apparatus may apply a suction force onto a surface of the collectible adjacent the loading tray. For example, 3604 may be performed by processor 120 of the system 100. The grading apparatus may apply the suction force onto the surface of the collectible adjacent the loading tray, such that the suction force pulls the collectible towards the loading tray such that the collectible is substantially flat. In some aspects, one or more openings of the loading tray may allow the suction force to pull the collectible towards the loading tray.
At 3606, the grading apparatus may deionize the collectible. For example, 3606 may be performed by processor 120 of the system 100. The grading apparatus may deionize the collectible in order to remove one or more particles from the collectible and balance an ion level on the collectible. The grading apparatus may deionize the collectible to receive the at least one image of the collectible. In some aspects, the deionized collectible may prevent the one or more particles from being attracted to the collectible. In some aspects, deionizing the collectible may remove the one or more particles from a region between the collectible and an image acquisition device.
At 3608, the grading apparatus may apply one or more lighting conditions to the collectible. For example, 3608 may be performed by processor 120 of the system 100. The one or more lighting conditions may assist in identifying one or more defects on the collectible. In some aspects, one or more lighting conditions may comprise at least one of a refractive light from one or more different angles. In some aspects, the one or more lighting conditions may create one or more shadows on the collectible. The one or more shadows are measured to identify raised or depressed surface areas on the collectible. In some aspects, the one or more lighting conditions may comprise infrared (IR) lighting. The IR lighting is configured to measure a thickness of the collectible. In some aspects, the one or more lighting conditions may create one or more shadows on the collectible. The at least one image, individually, or a compositing of a plurality of images, is measured to identify raised or depressed surface areas of the collectible.
At 3610, the grading apparatus may apply at least one processing routine to the at least one image. For example, 3610 may be performed by processor 120 of the system 100. The at least one processing routing may be applied in response to the grading apparatus receiving the at least one image of the collectible.
At 3612, the grading apparatus may generate a topological image of the collectible. For example, 3612 may be performed by processor 120 of the system 100. In some aspects, the topological image may comprise a plurality of images of the collectible. The plurality of images may comprise a series of images of the collectible lighted under different lighting conditions. One or more surface imperfections on the collectible may be identifiable using the topological image. In some aspects, the at least one processing routine may be utilized to generate the topological image, such that the topological image may be used to identify one or more defects. The topological image may be used to score the identified one or more defects. In some aspects, the one or more surface imperfections may comprise a card stock manipulation, where the topological image identifies variations in a surface topology or thickness of the collectible based on an expected surface topology or thickness of the collectible.
At 3614, the grading apparatus may overlay the topological image of the collectible onto the at least one image of the collectible. For example, 3614 may be performed by processor 120 of the system 100. An opacity of the topological image of the collectible may be adjustable as overlaid onto the at least one image of the collectible and is used to identify one or more defects. The topological image may be used to score the identified one or more defects. In some aspects, adjusting the opacity of the topological image may allow one or more surface imperfections on the collectible identified using the topological image to be compared against the at least one image of the collectible.
At 3616, the grading apparatus may identify one or more regions of the collectible. For example, 3616 may be performed may processor 120 of system 100. The one or more regions may comprise a portion of the collectible. The one or more regions may be prioritized based on an identifiable content of the collectible within the portion of the collectible. In some aspects, a first region of the one or more regions may comprise facial features of the collectible, where the first region is prioritized for grading. In such aspects, a box may be generated around the first region.
At 3618, the grading apparatus may assign a deduction to each defect identified on the collectible. For example, 3618 may be performed by processor 120 of system 100. The deduction may be used to score the identified defects. The grade report of the collectible may comprise one or more deductions for one or more defects. In some aspects, the deduction may be applied to each defect identified on a front surface of the collectible and to each defect identified on a back surface of the collectible.
At 3620, the grading apparatus may identify at least one defect of the collectible by including at least one indicator on an image that comprises the at least one defect. For example, 3620 may be performed by processor 120 of system 100. The at least one indicator may comprise an indicator that indicates a defect location based on horizontal and vertical coordinates. In some aspects, the grade report may comprise a detailed defect report of the at least one defect of the collectible. The detailed defect report may allow for the at least one defect of the collectible to be viewable. The at least one defect may be identified by the at least one indicator.
At 3622, the grading apparatus may examine one or more edges of the collectible to determine whether at least one of the one or more edges is inconsistent with other edges. For example, 3622 may be performed by processor 120 of system 100. The determination of an inconsistent edge may be based at least on the at least one processing routine that detects variations or inconsistencies on one or more edges.
At 3624, the grading apparatus may generate a grade report of the collectible. For example, 3624 may be performed by processor 120 of the system 100. The grading apparatus may generate the grade report of the collectible based at least one results of the at least one processing routine. In some aspects, the apparatus for grading the collectible may be comprised within a remote grading unit. Location data captured at the remote grading unit may identify a physical location of the remote grading unit and the collectible submitted for grading. In some aspects, one or more steps of grading the collectible may be performed by the remote grading unit. In some aspects, location data may be stored within a database to generate statistical data indicating usage and an identity of collectibles submitted for grading. In some aspects, the remote grading unit may be configured to perform at least one of an image acquisition of the collectible, a verification of the collectible, generation of the grade report, printing of an encasement, or an encasing of a graded collectible. The remote grading unit in conjunction with a centralized grading unit may be configured to grade the collectible. The remote grading unit or the centralized grading unit may perform one or more of image acquisitions of the collectible, the verification of the collectible, the generation of the grade report, or the encasing of the graded collectible. In some aspects, the grade report may comprise a scoring within a range of 100 to 1000 point scoring. The scoring may be scaled to correlate to a collectible score based on a range of 1-10 grade value. The grade report comprises one or more different scoring metrics.
The system 3700 may comprise an encasing apparatus 3704 configured to encase a graded collectible within a protective slab. The encasing apparatus 3704 may be configured to print information derived from, and related to, at least one of identification, the results of the at least one processing routine, a collectible grade, and an authentication of the collectible printed on the protective slab. The information may be printed on the protective slab using an ultra-violet (UV) printer with UV ink. The information may comprise at least a security indicator and an identification indication. The security indicator and the identification indication may be viewable from opposing sides of the protective slab, for example as shown in
The system 3700 may comprise an imaging device 3706 configured to capture at least one image of the collectible within the protective slab. The at least one image of the collectible may be stored on a database. The at least one image of the collectible may be available, from the grading apparatus, for submission to an online platform for sale.
The system 3700 may comprise an exchange 3708 configured to operate as a marketplace to offer the graded collectible for sale. The exchange may be limited to graded collectibles that have been graded by the grading apparatus. In some instances, the marketplace further offers the graded collectibles, graded by the grading apparatus, with a put option including a right, as holder of the put option, to sell the graded collectible at a future time within a specified time and at a specified price, or a call option including a right, as holder of the call option to purchase the graded collectible at the future time within the specified time and at the specified price. The exchange may be configured to offer financing to purchasers of the graded collectibles or insurance to insure the purchaser of the graded collectibles that the collectible is graded by the apparatus or insurance against loss of the collectible graded by the apparatus. The call option is a contract between a buyer and a seller for the buyer to purchase a specified collectible until a defined expiration date. The call option may comprise a future call option. The future call option is for a collectible not yet graded by the grading apparatus or of a collectible anticipated to be available in the future. The put option comprises an option to sell a specified collectible at a put option price, where an actual price of the specified collectible is less than the put option price. The graded collectible may comprise a defect free collectible such that the defect free collectible is graded directly from an unopened case, box, or pack of manufactured collectibles.
The system 3700 may comprise a video recording system 3710 configured to record at least a portion of a grading process of the collectible. A recording of at least the portion of the grading process of the collectible may be available for sale or utilized for security purposes. At least the portion of grading process includes receipt of the collectible, an image acquisition of the collectible, printing information of the collectible, encasing of the collectible within the protective slab, grading of the collectible, or shipment of the graded collectible. The recording of the at least the portion of the grading process may be utilized for identifying the portion within the grading process, actual grading, authentication of the graded collectible, or security to identify a location of the collectible at a time an image or a part of the grading process of the collectible was last obtained.
The system 3700 may comprise a submission kit 3712 configured to be utilized for submitting the collectible for grading. The collectible submission kit may comprise a tracking device to track a location of the collectible submission kit. The submission kit may comprise a shield configured to receive the collectible, a sleeve configured to protect the collectible, where the sleeve is received by the shield, a deck box (e.g., 2600) configured to store the collectible during transit, and a tracking device to monitor the collectible while in transit. In some aspects, the deck box may be configured to store one or more collectibles, as shown for example at
The system 3700 may comprise a foil wrap apparatus 3716 configured to wrap the graded collectible. The foil wrap apparatus 3716 may be configured to wrap the graded collectible, graded by the grading apparatus, within the protective slab within a foil wrapping. The foil wrapping may comprise at least one of a tracking device, information related to the graded collectible, or a grading of the graded collectible.
Aspects of the disclosure may comprise high resolution scanner images or high magnification lenses and/or high-resolution digital cameras to capture images with detail that is imperceptible to the naked eye even using hand held magnifiers, as is currently used in conventional grading. Precise imaging tools may, for example, be utilized to measure thickness, curves, indents, depth, breadth, size, scratches, dents, creases, color, area, length, etc. Precise location and stability of tools in an enclosed and controlled environment are utilized to assure consistency of results. Because the human element is removed, grading of a given collectible 116, when repeated, will provide within known fixed filters and proprietary algorithms, a statistically valid and similar result, over and over again. Environmental factors are removed from the process such as uncontrolled light, physical movement, distance of lens from Subject, angle, type and configuration of lights and variations in the application of image processing algorithms, as well as fatigue, emotional variance, different eyesight capabilities and different human weighting of defects from different human graders to assure consistency. However, in some aspects, an image of the collectible may be taken from a location remote and/or external to the computerized system utilizing various different types of imaging devices, such as but not limited to, smart phones, digital cameras, and the like. In such aspects, the grading of the collectible will be based on the external image submitted to the computerized system.
The computerized system 100 may utilize many image processing algorithms to examine all the criteria necessary for grading. The computerized system 100 may be implemented as a system utilizing a comprehensive examination and analysis of all grading aspects of a collectible 116 for the purpose of grading a given collectible 116 in a consistent manner. A precise and accurate grade must be able to be similarly reproduced on a given collectible 116 when such collectible 116 is tested repeatedly. A precise and accurate grading system must use grading criteria that are standardized and consistently applied to all collectibles 116 if it is to provide a basis for comparing one collectible to another when the collectibles are not similar, such as a 1952 Topps Mickey Mantle Baseball card with a 1957 Topps Mickey Mantle baseball card.
There is no grading system in use today that is completely automated, objective, and not, in part, relying on manual grading input. These grading systems lead to errors, inconsistent grades, varying points of grading emphasis by individual graders and re-grading of the same card resulting in different grades. Manual systems may also provide higher grades given to more “important” customers or larger users of the grading service thus depriving the smaller customer from playing on a level playing field. Grading companies state publicly that graders do not know the owner of a collectible 116 but this statement neither assures that a non-grader/supervisor does not know the collectible 116 owner's identity nor that the non-grader/supervisor does not have the means to influence a grade. Further, it is equally important that a card grade may be influenced as it is that the market believes that it could be influenced.
TAG Proof is a card that is identified as virtually perfect and does not have any visible, apparent, and/or significant defects. Similar in concept to a Proof coin issued by the U.S. Mint, the TAG Proof may be issued by the manufacture or by TAG in a controlled environment. TAG may go to the manufacture's printing facilities and grade cards as they are printed. TAG will wear gloves; human hands will not touch the cards. As TAG identifies cards that receive a perfect grade (Proof) subject to permitted system variance they will be placed in holders and marked as “Proof”. The TAG Proof card can be the standard upon which other cards of the same type are compared against to determine the highest quality and most valuable card condition.
Although the present disclosure and its advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the technology of the disclosure as defined by the appended claims. For example, relational terms, such as “above” and “below” are used with respect to a light source or a collectible. Of course, if the light source or collectible is inverted, above becomes below, and vice versa. Additionally, if oriented sideways, above and below may refer to sides of the light source or collectible. Moreover, the scope of the present application is not intended to be limited to the particular configurations of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the disclosure, processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding configurations described herein may be utilized according to the present disclosure. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
The various illustrative logical blocks, and modules described in connection with the disclosure herein may be implemented or performed with a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the disclosure may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM, flash memory, ROM, EPROM, EEPROM, registers, hard disk, a removable disk, a CD-ROM, solid state storage, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal. In yet other aspects, the processor can be remote to the storage medium and accesses the storage medium through a linked connection.
In one or more exemplary designs, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, solid state, or any other medium that can be used to carry or store specified program code means in the form of instructions or data structures and that can be accessed by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
In the present disclosure, the processor may serve as a structure for computer-implemented functions as described herein because the function(s) described in one or more aspects of the present disclosure are coextensive with the processor itself. Further, such a processor may serve as structure for functions that may be achieved by a general purpose computer without special programming, because the coextensive functions include receiving data, storing data, processing data, etc. Further, the present disclosure are removed from the abstract, and do not merely limit the use of an abstract idea to a particular technological environment. The present disclosure expands basic building blocks beyond the mere sum of the parts, at least for the reason that the present disclosure provides faster, more consistent, and more reliable results than obtainable with current methods and devices.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
This application is a continuation in part application of Ser. No. 17/194,056 to Stephen Kass et al., filed on Mar. 5, 2021, which is a continuation application of Ser. No. 16/664,485 to Stephen Kass et al., filed on Oct. 25, 2019, now U.S. Pat. No. 10,942,933, which is a continuation application of Ser. No. 15/964,546 to Stephen Kass et al., filed on Apr. 27, 2018, now U.S. Pat. No. 10,459,931, which is a continuation application of Ser. No. 15/706,543 to Stephen Kass et al., filed on Sep. 15, 2017, now U.S. Pat. No. 10,146,841, which is a continuation application of Ser. No. 15/000,989 to Stephen Kass et al., filed on Jan. 19, 2016, now U.S. Pat. No. 9,767,163, which claims the benefit of priority of U.S. Provisional Application Ser. No. 62/104,606 to Stephen Kass et al., which was filed on Jan. 16, 2015. The contents of Ser. Nos. 15/000,989, 15/706,543, 15/964,546, 16/664,485, 17/194,056, and 62/104,606, including their drawings, schematics, diagrams, and written description, are hereby incorporated in their entirety by reference.
| Number | Date | Country | |
|---|---|---|---|
| 62104606 | Jan 2015 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16664485 | Oct 2019 | US |
| Child | 17194056 | US | |
| Parent | 15964546 | Apr 2018 | US |
| Child | 16664485 | US | |
| Parent | 15706543 | Sep 2017 | US |
| Child | 15964546 | US | |
| Parent | 15000989 | Jan 2016 | US |
| Child | 15706543 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 17194056 | Mar 2021 | US |
| Child | 17805846 | US |
