This application claims the benefit of utility patent application having Ser. No. 10/921,294 filed on Aug. 19, 2004
1. Field of the Invention:
The present invention relates to a method, a system and a computer program product for determining the location of objects in an environment. More particularly, the present invention relates to a method, a device and a computer program product for determining the location of the objects in environments where the color of the object is not naturally found.
2. Description of the Prior Art:
There are many circumstances where an object is lost and determining its location is difficult due to the characteristics of the environment in which it has been lost. One such circumstance occurs during the playing of the sport of golf. Typically, the sport of golf is played on terrain having a variety of characteristics, such as grass, sand, trees, water, a specified distance, etc. It is not uncommon for a golf ball to become lost while playing golf due to the characteristics of the environment in which it is played. Once a golf ball is lost, a substantial amount of time can be spent trying to find it. This results in an increase of playing time for the player who lost the ball, as well as other players playing behind or with the player. In cases where the golf ball cannot be located, the player who lost the ball is accessed a penalty stroke increasing the player's final score.
Accordingly, there is a need for a device that detects and determines the location of an object in an environment having a variety of characteristics. There is further need for the device to be mobile. There is a further need for the device to detect the location of an object over long distances. There is a need for the device to be operable in a variety of lighting conditions. There is a need for the device to reduce glare and related image artifacts. There is a need for the device to reduce multiple reflections and shadowing in the detection of the object. There is a need for the device to decrease the amount of time required to locate an object.
According to embodiments of the present invention, a method, a device and a computer program product for determining the location of an object in an environment are provided. The method receives an optical image of an environment and converts the optical image of the environment into a live color digital image of the environment consisting of charged signals, where each charged signal was generated by a pixel in an array of a Charged Coupler Device (CCD) by photoelectric conversion.
The live color digital image depicts an environment having one or more similar objects. Software performs an analysis of the live color digital image to detect and determine the location of the one or more objects in the live color digital image of the environment by using color and shape characteristics of the one or more objects. The software uses a range of the visible portion of the color space uniquely identified for the type of object in that environment to detect and determine the location of the one or more objects in the live color digital image of the environment. When the object is a golf ball, color is defined by reflection of light and by UV stimulated emission of blue fluorescence due to the brighteners incorporated in the composition of golf balls. Color in this application may be due to the reflection of light, stimulated emission such as fluorescence, phosphorescence and alike processes separately or in combination. In the presence of sufficient sun light, the color of a golf ball is expected to be unique, a blue enhanced white not naturally found in objects. Furthermore, because a lost golf ball is only partially visible, where 1% or more of its surface may be unobstructed, the color of the golf ball is not identifiable as an object. In general, the image of a lost golf ball occupies a very small percentage of the image and statistical approaches are needed to identify the pixels for a lost golf ball.
The range of the color space is based at least in part on the color spaces identified for the type of object, such as a golf ball having a blue enhanced white not naturally found in objects, under various lighting conditions in the environment where the type of object would be lost. The color spaces for the object are defined by analyzing the color spaces obtained from the object in live color digital images of the object under the various lighting conditions in a training mode and storing the color spaces. The object is detected by using an algorithim that identifies pixels in the live color digital image that corresponds with a color space in the range of color spaces. Once a pixel is identified, it is recorded. Recorded pixels are analyzed to determine whether there are clusters of pixels that meet a particular criteria. The image may be filtered using polarization to eliminate glare.
The above described features and advantages of the present invention will be more fully appreciated with reference to the detailed description and appended figures in which:
a-4d depict exemplary color space diagrams of an object shown in a color digital image.
The present invention is now described more fully hereinafter with reference to the accompanying drawings that show embodiments of the present invention. The present invention, however, may be embodied in many different forms and should not be construed as limited to embodiments set forth herein. Appropriately, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present invention.
According to embodiments of the present invention, a method, a device and a computer program product for determining the location of an object in an environment are provided. The method receives an optical image of an environment and converts the optical image of the environment into a live color digital image of the environment consisting of charged signals, where each charged signal was generated by a pixel in an array of a Charged Coupler Device (CCD) by photoelectric conversion.
The live color digital image depicts an environment having one or more similar objects. Software performs an analysis of the live color digital image to detect and determine the location of the one or more objects in the live color digital image of the environment by using color and shape characteristics of the one or more objects. The software uses a range of the visible portion of the color space uniquely identified for the type of object in that environment to detect and determine the location of the one or more objects in the live color digital image of the environment. When the object is a golf ball, color is defined by reflection of light and by UV stimulated emission of blue fluorescence due to the brighteners incorporated in the composition of golf balls. Color in this application may be due to the reflection of light, stimulated emission such as fluorescence, phosphorescence and alike processes separately or in combination. In the presence of sufficient sun light, the color of a golf ball is expected to be unique, a blue enhanced white not naturally found in objects. Furthermore, because a lost golf ball is only partially visible, where 1% or more of its surface may be unobstructed, the color of the golf ball is not identifiable as an object. In general, the image of a lost golf ball occupies a very small percentage of the image and statistical approaches are needed to identify the pixels for a lost golf ball.
The range of the color space is based at least in part on the color spaces identified for the type of object, such as a golf ball having a blue enhanced white not naturally found in objects, under various lighting conditions in the environment where the type of object would be lost. The color spaces for the object are defined by analyzing the color spaces obtained from the object in live color digital images of the object under the various lighting conditions in a training mode and storing the color spaces. The object is detected by using an algorithim that identifies pixels in the live color digital image that corresponds with a color space in the range of color spaces. Once a pixel is identified, it is recorded. Recorded pixels are analyzed to determine whether there are clusters of pixels that meet a particular criteria. The image may be filtered using polarization to eliminate glare.
In the
The input system 104 is coupled to circuitry 106 and provides an analog image signal to the circuitry 106. The circuitry 106 samples the analog image signal and extracts the voltage that is proportional to the amount of light which fell on each pixel of the charge-coupled device sensor of the input system 104 using color components R (red), G (green) and B (blue). Programmable gain amplifier (PGA) 108 is coupled to circuitry 106, amplifies the voltages to the proper range and provides the voltages as input to analog-to-converter 110. Analog-to-digital converter (ADC) 110 is coupled to CPU 102 and converts the voltage to a digital code suitable for further digital signal processing by CPU 102. The CPU 102 is a microprocessor, such as an INTEL PENTIUM® or AMD® processor, but can be any processor that executes program instructions in order to carry out the functions of the present invention.
In the
In the
An exemplary flow diagram of an embodiment for determining the location of an object in a particular environment is shown in
The target color space for a lost golf ball depends on both light reflected from the golf ball and light emitted from the golf ball, i.e., fluorescence of the golf ball. The fluorescence is due to brighteners added to golf ball to improve their appearance. Such brighteners absorb UV from sunlight and re-emit the light at lower energy as blue light. Blue color added to white is well known to improve the “whiteness” of an object. The practice of adding brighteners to golf ball is common for this reason. Hence, the color of a golf ball has two components, reflected light and blue fluorescence.
In defining a target color space, color shifts caused by the specific lighting conditions of the particular type of object must be considered and included in the target color space for the type of object. Accordingly, the color shifts of the type of object must be determined. This includes color shifts caused by “global” lighting, such as sunny versus cloudy weather, as well as “local” lighting, such as in grass or under a bush. For purposes of our invention, we define “white” as the color of a typical golf ball.
Turning here briefly to
Returning here to
In step 304, the digital color image is processed to detect the location of the object in the environment. This includes, but is not limited to, identifying pixels in the live color digital image that matches a color space in the target color space defined for the type of object. In the
In step 306, a decision statistic is defined that represents the likely characteristics of the type of object. In an embodiment of the present invention, the intensity of the background can be used as a decision statistic. The intensity of the background can be determined by processing the color digital image a second time. With an image-specific histogram of the background intensity, a lower-bound threshold for the expected target intensity can be defined, such as at the 90%, 95%, or 99% level of the background intensity. The pixels whose locations are stored can be screened using this criterion, with those pixels not meeting the intensity specification removed.
In an embodiment of the present invention, the size of the type of object can be used as a decision statistic. The size of the type of object can be used to identify the object by determining the diameter, such as a golf ball measured in pixels. This value can serve as a cluster distance. The pixels whose locations are stored can be screened using this criterion by collecting into groups, or clusters, those pixels that are within a cluster distance of each other.
In step 308, it is determined whether the object is identified in the environment based on one or more statistics. A statistic includes color space information, and may also include intensity information and/or cluster information. A statistic may also include weighting values from any reference images collected. The preferred approach is to define one statistic, but it is obvious that multiple statistics could be defined and used with this method. In step 310, the object is reported if identified, such as by display 118.
While specific embodiments of the present invention have been illustrated and described, it will be understood by those having ordinary skill in the art that changes can be made to those embodiments without departing from the spirit and scope of the invention. For example, while the present invention concentrates on a single color digital image and stationary lost object analysis, it is understood that information from a series of images, a moving object or a specific object might advantageously be used as well. Also, while our application to golf balls has us discussing UV and visible light, the method is not dependent on this choice.
Number | Date | Country | |
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Parent | 10921294 | Aug 2004 | US |
Child | 11446271 | Jun 2006 | US |