This disclosure relates generally to imaging equipment such as scanners, and more particularly to method and apparatus for calibrating imaging equipment.
Imaging equipment, or scanning devices such as scanners, are used to collect data from documents and translate the collected data for digital storage and processing. During the course of scanning large volumes of documents, scanners may experience inaccuracies in data collection due to camera profiling, camera adjustments or bulb replacement
In order to promote precision and accuracy of a batch-document scanning process, it is desirable to ensure that quality standards for the scanners are continually met. Improved method and apparatus for calibrating imaging equipment are needed.
The above-mentioned problems and others not expressly discussed herein are addressed by the present subject matter and will be understood by reading and studying this specification.
Disclosed herein, among other things, are method and apparatus for calibrating imaging equipment. According to one embodiment of a method, a calibration deck of timing sheets is prepared. The calibration deck includes a sheet with a series of reference marks that help determine the amount of skew, a sheet with objective scoring bubbles that are all filled in with black ink, a grey scale bubble sheet having a predetermined number of shades between black and white, and a sheet with objective scoring bubbles that are all unfilled, or white. The timing sheets are scanned on a scanner, and results from scanning the calibration deck are compared to an industry standard baseline.
One aspect of the disclosure includes a system for calibrating a scanner. According to an embodiment, the system includes a calibration deck of sheets. The calibration deck includes, a sheet with a series of reference marks, a sheet with objective scoring bubbles that are all filled in with black ink, a grey scale bubble sheet having a predetermined number of shades between black and white, and a sheet with objective scoring bubbles that are all unfilled, or white. According to various embodiments, the calibration deck is adapted to be scanned on the scanner, and where results from scanning the calibration deck are compared to an industry standard baseline. The system includes a display for depicting results for at least one scanner, in an embodiment.
This Summary is an overview of some of the teachings of the present application and not intended to be an exclusive or exhaustive treatment of the present subject matter. Further details about the present subject matter are found in the detailed description and appended claims. The scope of the present invention is defined by the appended claims and their legal equivalents.
The following detailed description of the present subject matter refers to subject matter in the accompanying drawings which show, by way of illustration, specific aspects and embodiments in which the present subject matter may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the present subject matter. References to “an”, “one”, or “various” embodiments in this disclosure are not necessarily to the same embodiment, and such references contemplate more than one embodiment. The following detailed description is demonstrative and not to be taken in a limiting sense. The scope of the present subject matter is defined by the appended claims, along with the full scope of legal equivalents to which such claims are entitled.
The present subject matter generally relates to method and apparatus for calibrating imaging equipment. A computer application for calibrating imaging equipment is referred to as a calibration facilitator. To ensure quality standards are continually met on scanners, the calibration facilitator application is used to compare baseline calibration decks against scanner output. In an embodiment, IBML scanners are calibrated. However, other types of scanners can be calibrated without departing from the scope of this disclosure.
The present subject matter is part of a system whose purpose is to convert education assessments (standardized tests, etc.) from paper format to electronic format, thereby providing a means to score both objective (bubbled) fields and writing responses. In addition to scoring fields, the system associates students to their scanned data and achieves a high level of quality in scanned results. Documents are received and scanned, images are generated and passed through processes and applications before data is handed off to peripheral systems.
The capture of images on a scanner involves several factors. The setup of the camera, the brightness of the light source, and the speed and consistency of the paper as it travels down the track are all factors that can affect the quality and darkness of the captured images. As each bubble response must be read on a grayscale range (16 levels from 0 to F), the darkness in which an image is captured must be precise and consistent across all scanners in the system. Most scanners do not have any built-in features to ensure that the scanners are capturing images to a set standard. Therefore, a scanner with a calibration mechanism, which is calibrated to an industry standard, is used to ensure accuracy of all scanners in the system. By scanning a set of documents on a scanner calibrated to the industry standard, and then obtaining data about that scan, the data can be used as a calibrated “baseline.” When the same set of documents is scanned on other “uncalibrated” scanners (such as an IBML scanner, in an embodiment), the results are compared to the calibrated baseline to create a profile that defines how the image would need to change to match the baseline. Once a scanner has gone through the calibration process, every subsequent image captured on the scanner can be adjusted based on the created calibrated profile. This process is repeatable, and is done periodically to ensure that other factors have not changed how an image is being captured relative to the baseline.
The calibration facilitator application is a user-based application which serves multiple roles for the calibration environment. It can be used to scan and process calibration decks, review the results of previous calibration scans, import baseline files generated when a calibration deck is scanned on an industry standard calibrated scanner (such as on NCS 5000 scanner, in an embodiment), and perform maintenance of a calibration deck. A calibration deck is a set of printed documents designed for capturing. In an embodiment, one part of the deck includes 16 documents, each having 256 bubbles placed in various patterns. Bubbles refer to any two-dimensionally closed form adapted to be filled in with a writing utensil, such as but not limited to: a circle, an ellipse, a square, and a rectangle. Bubbles with other shapes and sizes can be used without departing from the scope of this disclosure. Each of the bubbles on the 16 documents is defined to a certain grayscale level, from white to black. In this embodiment, two additional documents in the deck have all 256 white bubbles (used to ensure paper darkness is capturing consistently across the image), and two other documents have 256 black bubbles (used to ensure black captures consistently). This embodiment further includes 30 documents that are identical and have a series of reference marks (or “T” marks, in an embodiment) printed at precise distances (both vertically and horizontally) across the form. According to various embodiments, reference marks may be in any convenient shape for capturing by the scanner, including letters or other figures. The reference marks are used to make sure the image is capturing at the right speed on the scanner A threshold is used to compare the scanner to the calibrated industry scanner, and if the scanner is outside tolerances, a maintenance person must service the scanner before continuing. For example, if 3 or 4 marks are blacker than “0” on a hexadecimal scale, then the scanner fails the calibration. The depicted embodiments do not calibrate the scanners; rather check the scanners to ensure they remain in calibration. Using multiple (16 in an embodiment) different sheets with grayscale colors provides better resolution to ensure proper calibration of scanners, and allows results to be depicted more accurately.
According to various embodiments of the method, comparing results includes determining the amount of skew of an image on a sheet, determining the amount of stretch of an image on a sheet, measuring track speed of the scanner, and/or determining the proportionality of an image on a sheet. The method further includes automatically interpreting results using a threshold, in an embodiment. Interpreting the results includes proceeding if the score is acceptable within a predefined tolerance, and also includes providing a notification of an unacceptable result so that the scanner can be manually recalibrated, in various embodiments. In various method embodiments, a status bar is provided showing the relative completion of calibration deck processing. In an embodiment, the relative completion is measured in percent. The method also includes determining the amount of one or more of shrinkage, stretch, skew or other distortions of a scanned page, in various embodiments.
Comparing results of the calibration deck scan to an industry standard baseline includes comparing the results to a scanner with a self-calibration feature, such as an NCS scanner, in an embodiment. The comparison establishes a darkness level, in various embodiments. According to various embodiments, each calibration deck can only be used a predetermined number of times. For example, each calibration deck can be scanned 10 times before it is replaced. An authorized user can adjust the number of uses per calibration deck, in an embodiment. For example, in
One aspect of the disclosure includes a system for calibrating a scanner. According to an embodiment, the system includes a calibration deck of sheets. The calibration deck includes, a sheet with a series of reference marks, a sheet with objective scoring bubbles that are all filled in with black ink, a grey scale bubble sheet having a predetermined number of shades between black and white, and a sheet with objective scoring bubbles that are all unfilled, or white. According to various embodiments, the calibration deck is adapted to be scanned on the scanner, and results from scanning the calibration deck are compared to an industry standard baseline. The system includes a display for depicting results for at least one scanner, in an embodiment.
The display includes a status bar showing the relative completion of calibration deck processing, in an embodiment. The relative completion can be measured in percent. In various embodiments, the display includes a notification of an unacceptable result so that the scanner can be manually recalibrated. In one embodiment, at least sixteen grey scale bubble sheets are included having a predetermined number of shades between black and white. The grey scale bubble sheet has 256 shades, in an embodiment. At least 30 sheets with reference marks (such as a series of “T”'s, in an embodiment), at least two sheets with objective scoring bubbles that are all filled in with black ink, and at least two sheets with objective scoring bubbles that are all unfilled, or white are included in various embodiments.
The calibration facilitator is an automated application and provides a status screen for a user. The status screen includes a scan batch, validate batch and batch status bar showing percent completion, in various embodiments. The results of the calibration deck scan are processed automatically using a threshold to determine whether a successful scan has been completed. If a successful (errors below the threshold) scan is completed on a scanner, processing continues without interruption on that scanner. If the scan is unsuccessful (errors above the threshold) for a scanner, a notification is made to provide instruction to a user that manual calibration of the identified scanner is required.
Scanned images include an equal number of image sheets from the scanner's top camera and from the scanner's bottom camera, in an embodiment. In addition to the images, a hexadecimal score (0-9, A-F) is captured for each target. The application provides the user with a programmatic comparison of the scanned image and the baseline calibration image, the output of which is displayed on a screen.
A reference mark locator application and a reference mark viewer application work together with the calibration facilitator. These applications help identify image capture problems. They work together to capture a series of measurements on scanned images and display the measurements and any patterns found to the user of the applications.
The reference mark locator application uses specially printed documents having known printing specifications. These documents have 140 reference marks (or T-marks, in an embodiment) printed in 14 rows and 10 columns. Each reference mark is printed at a precise distance from the other (0.75 inches, for example), both vertically and horizontally. After an image is captured of one of these documents on the scanner, it is fed into the locator application and all of the T-marks are programmatically located. The straight-line distance between each mark and its neighboring marks is calculated and output both as an annotation on the image, as well as into a text file. Using 0.75 inches as an example, all distances would be exactly 150 pixels on a perfect image (assuming 200 dots per inch (dpi)). In one embodiment, this application is used with a batch of 50 documents, scanned twice so images off both the top and bottom camera of IBML scanners are captured.
The reference mark viewer application is used to view the results of the batch of documents scanned using the reference mark locator. Once a batch is selected, the user can look at the measurement patterns on all of the images of the batch in rapid succession. The user can set color thresholds to make the viewing easier. For example, a user can set the application to identify all measurements of 149 pixels or less as green, all measurements of 151 pixels or more as red, and all measurements of exactly 150 pixels as white. Examining the results will show a pattern on multiple images where the measurements are consistently too big or too small, and the at-fault scanner can be identified and re-calibrated. It may be that the belt speeds are too fast, too slow, out of synch, or that the transition points between rollers on the scanner are flawed. The results may show something wrong from top to bottom or left to right over the entire image, or that specific rows or columns of measurements are consistently off in the image. The tolerance for errors depends upon the application the scanner is used for. For example, for certain scanner applications involving objective test answer sheets, measurements between 148 and 152 pixels are acceptable.
Completed test booklets are boxed, illustrated at 208, for shipping to a test-processing center 210. The boxes include an identifier 212, such as a bar code for example. Upon arriving at the test-processing center 210, the boxes of test booklets are unloaded at 214. The test booklets are removed from the boxes and sorted at 216. At 220, the test booklets are cut into loose pages. These loose pages are reconciled to ensure that all of the pages for each test booklet are accounted for. Reading devices 222, 224, and 226, such as bar code scanners for example, are used to read the identifiers 223 and identify the boxes, read the identifiers 225 and identify the test booklets, and read the identifiers and identify the pages. In one embodiment, the image field definition system identifies the identifying markings for the pages.
The test pages are graded or scored at 228. In one embodiment, objective scoring tasks, such as multiple choice questions for example, are scored using scoring of tests from images 230. In one embodiment, open-ended scoring tasks are scanned at scanning stations 232, are stored in a queue, and are distributed by a dealer 234 to human readers 235 who evaluate the open-ended scoring tasks. Reports 236 of the score results are provided at 237.
A server in the test-processing center is used to perform a variety of tasks with the scanned data, as discussed herein. In one embodiment, the server includes priority information, as illustrated via lines 238, 240, 242, 244 and 246; the priority information is available at various places along the process. In one embodiment, for example, the reading device(s) 222 determines which of the boxes should proceed for further processing before other boxes. In one embodiment, the reading device(s) 224 determine which of the test booklets should proceed for further processing before other test booklets. In one embodiment, the reading device(s) 226 determine which of the pages (or test items on the pages) should proceed for further processing before other pages (or test items on the pages). In one embodiment, for example, the priority information is used in the scoring system 228 to determine which test items should be scored before other test items. In one embodiment, for example, the priority information is used to determine which reports should be provided before other reports 236.
This application is intended to cover adaptations and variations of the present subject matter. It is to be understood that the above description is intended to be illustrative, and not restrictive. The scope of the present subject matter should be determined with reference to the appended claim, along with the full scope of legal equivalents to which the claims are entitled.
This application claims the benefit of provisional U.S. patent application Ser. No. 60/981,750, filed on Oct. 22, 2007, which is hereby incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
4813077 | Woods et al. | Mar 1989 | A |
4817179 | Buck | Mar 1989 | A |
4827330 | Walsh et al. | May 1989 | A |
4837842 | Holt | Jun 1989 | A |
4967354 | Buchanan | Oct 1990 | A |
4978305 | Kraft | Dec 1990 | A |
5001769 | Reid-Green et al. | Mar 1991 | A |
5004896 | Serrell et al. | Apr 1991 | A |
5041874 | Nishimori et al. | Aug 1991 | A |
5194966 | Quardt et al. | Mar 1993 | A |
5313291 | Appel et al. | May 1994 | A |
5321611 | Clark et al. | Jun 1994 | A |
5363318 | McCauley | Nov 1994 | A |
5433615 | Clark | Jul 1995 | A |
5452379 | Poor | Sep 1995 | A |
5557515 | Abbruzzese et al. | Sep 1996 | A |
5672060 | Poor | Sep 1997 | A |
5735694 | Clark et al. | Apr 1998 | A |
5825947 | Sasaki et al. | Oct 1998 | A |
5832100 | Lawton et al. | Nov 1998 | A |
5907742 | Johnson et al. | May 1999 | A |
5987149 | Poor | Nov 1999 | A |
5987302 | Driscoll et al. | Nov 1999 | A |
6141120 | Falk | Oct 2000 | A |
6173154 | Kucinski et al. | Jan 2001 | B1 |
6183261 | Clark et al. | Feb 2001 | B1 |
6204873 | Shimazaki | Mar 2001 | B1 |
6256111 | Rijavec | Jul 2001 | B1 |
6321052 | Yamashina et al. | Nov 2001 | B1 |
6366759 | Burstein et al. | Apr 2002 | B1 |
6404517 | Chao | Jun 2002 | B1 |
6459509 | Maciey et al. | Oct 2002 | B1 |
6471352 | Akahira | Oct 2002 | B2 |
6526258 | Bejar et al. | Feb 2003 | B2 |
6532026 | Takahashi et al. | Mar 2003 | B2 |
6645029 | Akahira | Nov 2003 | B2 |
6714321 | Rao et al. | Mar 2004 | B2 |
6832825 | Nishikori et al. | Dec 2004 | B1 |
6947571 | Rhoads et al. | Sep 2005 | B1 |
7027187 | Zuber | Apr 2006 | B1 |
7084998 | Blair et al. | Aug 2006 | B2 |
7162198 | Kuntz et al. | Jan 2007 | B2 |
7295340 | Mestha et al. | Nov 2007 | B2 |
7406392 | Gedlinske et al. | Jul 2008 | B2 |
7411688 | Zhai et al. | Aug 2008 | B1 |
7474783 | Sharma et al. | Jan 2009 | B2 |
7505173 | Viturro et al. | Mar 2009 | B2 |
7516895 | Holoubek | Apr 2009 | B2 |
7573616 | Poor | Aug 2009 | B2 |
7630931 | Rachev et al. | Dec 2009 | B1 |
7692832 | Klassen | Apr 2010 | B2 |
7697166 | Bray | Apr 2010 | B2 |
7742991 | Salzmann et al. | Jun 2010 | B2 |
7831195 | Borchers | Nov 2010 | B2 |
7835043 | Gila et al. | Nov 2010 | B2 |
7992953 | Yorimoto et al. | Aug 2011 | B2 |
8102412 | Klemer et al. | Jan 2012 | B2 |
20010028916 | Akahira | Oct 2001 | A1 |
20010040979 | Davidson et al. | Nov 2001 | A1 |
20020054384 | Motamed | May 2002 | A1 |
20020126172 | Akiyama | Sep 2002 | A1 |
20020161772 | Bergelson et al. | Oct 2002 | A1 |
20030016263 | Takahashi et al. | Jan 2003 | A1 |
20030105721 | Ginter et al. | Jun 2003 | A1 |
20030118976 | Makishima et al. | Jun 2003 | A1 |
20030126001 | Northcutt et al. | Jul 2003 | A1 |
20030202029 | Bronswijk et al. | Oct 2003 | A1 |
20040114164 | Linder et al. | Jun 2004 | A1 |
20040117617 | Geller et al. | Jun 2004 | A1 |
20040130739 | Adam et al. | Jul 2004 | A1 |
20040131279 | Poor | Jul 2004 | A1 |
20040264771 | Sharma et al. | Dec 2004 | A1 |
20050024410 | Subirada et al. | Feb 2005 | A1 |
20050094170 | Ichitani | May 2005 | A1 |
20050172226 | Kobashi et al. | Aug 2005 | A1 |
20050206982 | Hattori | Sep 2005 | A1 |
20050213790 | Rhoads et al. | Sep 2005 | A1 |
20060028699 | Venable et al. | Feb 2006 | A1 |
20060077407 | Tanaka | Apr 2006 | A1 |
20060164700 | Hayashi | Jul 2006 | A1 |
20060193017 | Zuber | Aug 2006 | A1 |
20060195508 | Bernardin et al. | Aug 2006 | A1 |
20060227386 | Nuuja et al. | Oct 2006 | A1 |
20060285134 | Viturro et al. | Dec 2006 | A1 |
20060288279 | Yacoub et al. | Dec 2006 | A1 |
20070024657 | Zhang et al. | Feb 2007 | A1 |
20070024928 | Ono | Feb 2007 | A1 |
20070201112 | Motamed | Aug 2007 | A1 |
20070247681 | Klassen | Oct 2007 | A1 |
20080080027 | Mestha et al. | Apr 2008 | A1 |
20080152371 | Burry et al. | Jun 2008 | A1 |
20080225067 | Morino et al. | Sep 2008 | A1 |
20080316552 | Poor | Dec 2008 | A1 |
20090002724 | Paul et al. | Jan 2009 | A1 |
20090059321 | Buckley | Mar 2009 | A1 |
20090086230 | Reed | Apr 2009 | A1 |
20100231728 | Holub | Sep 2010 | A1 |
20100284041 | Warnes | Nov 2010 | A1 |
Number | Date | Country |
---|---|---|
0 374 892 | Apr 1997 | EP |
Entry |
---|
““Score Image” Processing of Constructed-Responses, Essays, and Writing Samples”, UNISCORE, Incorporated, (1992), 3 pgs. |
“Image Processing of Open-Ended Questions”, UNISCORE, Incorporated, (1992), 4 pgs. |
Cason, Gerald J, et al., “Integrated Test Scoring, Performance Rating and Assessment Records Keeping”, Innovations in Medical Education, Association of American Medical Colleges, Washington, D.C., Paper presented at the annual meeting of the Association of Medical Colleges., (Nov. 1, 1987), 2-20. |
Gathy, P, et al., “Computer-Assisted Self-Assessment (CASA) in Histology”, Computers Education., vol. 17, No. 2., (1991), 109-116. |
Reid-Green, Keith S, “A High Speed Image Processing System [Journal Paper]”, IMC Journal, vol. 26, No. 2, Mar.-Apr., USA, (1990), 12-14. |
Zuckerman, Ronald A, “Optical Scanning for Data Collection, Conversion & Reduction”, NITS, U.S. Department of Commerce, National Technical Information Service, August, Springfield, VA, USA, (1967), 49 pgs. |
U.S. Appl. No. 12/256,282, Non Final Office Action mailed Jan. 4, 2012, 12 pgs. |
U.S. Appl. No. 12/256,303, Non Final Office Action Mailed Jan. 5, 2012, 9 pgs. |
U.S. Appl. No. 12/256,303, Response filed Oct. 24, 2011 to Restriction Requirement mailed Jul. 23, 2011, 6 pgs. |
U.S. Appl. No. 12/256,303, Restriction Requirement mailed Aug. 23, 2011, 5 pgs. |
U.S. Appl. No. 12/256,339, Non Final Office Action mailed Jan. 10, 2012, 13pgs. |
U.S. Appl. No. 12/256,354, Restriction Requirement mailed Nov. 21, 2011, 8 pgs. |
“U.S. Appl. No. 12/256,282, Response filed Apr. 4, 2012 to Non Final Office Action mailed Jan. 4, 2012”, 7 pgs. |
“U.S. Appl. No. 12/256,303, Final Office Action mailed May 29, 2012”, 15 pgs. |
“U.S. Appl. No. 12/256,303, Response filed Apr. 5, 2012 to Non Final Office Action mailed Jan. 5, 2012”, 8 pgs. |
“U.S. Appl. No. 12/256,339, Response filed Apr. 10, 2012 to Non Final Office Action mailed Jan. 10, 2012”, 7 pgs. |
“U.S. Appl. No. 12/256,354, Non Final Office Action maied Mar. 1, 2012”, 8 pgs. |
“U.S. Appl. No. 12/256,282, Advisory Action mailed Dec. 31, 2012”, 3 pgs. |
“U.S. Appl. No. 12/256,282, Response filed Dec. 6, 2012 to Final Office Action mailed Aug. 6, 2012”, 7 pgs. |
“U.S. Appl. No. 12/256,339, Examiner Interview Summary mailed Nov. 23, 2012”, 3 pgs. |
“U.S. Appl. No. 12/256,339, Non Final Office Action mailed Jan. 9, 2013”, 16 pgs. |
“U.S. Appl. No. 12/256,339, Response filed Nov. 15, 2012 to Final Office Action mailed Sep. 7, 2012”, 9 pgs. |
“U.S. Appl. No. 12/256,354, Corrected Notice of Allowance mailed Jan. 17, 2013”, 2 pgs. |
“U.S. Appl. No. 12/256,354, Notice of Allowance mailed Feb. 1, 2013”, 6 pgs. |
“U.S. Appl. No. 12/256,354, Response filed Dec. 21, 2011 to Restriction Requirement mailed Nov. 21, 2011”, 5 pgs. |
Number | Date | Country | |
---|---|---|---|
60981750 | Oct 2007 | US |