Image analysis – Applications – Animal – plant – or food inspection
Reexamination Certificate
1998-03-26
2001-05-08
Mehta, Bhavesh (Department: 2621)
Image analysis
Applications
Animal, plant, or food inspection
C382S117000
Reexamination Certificate
active
06229905
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Technical Field of the Invention
The present invention relates generally to an animal identification system designed to identify animals such as horse or cattle using biometric analysis, and more particularly to an automatic animal identification system based on analysis of irial granules, which are unique for each individual.
2 Background Art
Typically, horse identification is achieved by visually perceiving physical features such as the color of hair or a pattern of white hair on the head or the body. Automatic identification systems have also been proposed which are designed to read identification data stored in a microchip embedded in the body of a horse.
For personal identification, automatic biometric systems are known which identify a particular human being based on image analysis of an iris of the human eye. Such techniques are taught in, for example, “High Confidence Visual Recognition of Persons by a Test of Statisical Independence”, J. G. Daugman (1993), IEEE Trans and “Pattern Analysis and Machine Intelligence”, 15(11), pp. 1148-1161.
Usually, animals such as horses or cattle have a three-dimensional protrusion called an irial granule, located around the pupil in the crystalline lens. The irial granule has a shape that is unique for each individual. Identification of animals such as horses or cattle can, thus, be performed based on analysis of the texture or shape of the irial granule.
The irial granule is, however, complex in shape and it is difficult to represent an outline of the irial granule using a geometric function having several parameters. Specifically, it is difficult for the conventional identification techniques as taught in the above references to extract the outline of the irial granule as image data.
The image of an eye captured by a videocamera in the open air may lack uniformity due to the use of an illuminator for the camera or entrance of external light, thus resulting in irregularity of image brightness of each of the pupil, the iris, and the irial granule or in dimness of the outline of the irial granule. A difficulty is, thus, encountered in extracting the outline of the irial granule through simple binary-coding or edge detection of the image.
SUMMARY OF THE INVENTION
It is therefore a principal object of the present invention to avoid the disadvantages of the prior art.
It is another object of the present invention to provide an animal identification system which is designed to extract from an image of an eye the shape of an irial granule required to identify a particular animal.
According to the first aspect of the present invention, there is provided an animal identification apparatus which comprises: (a) an outline extracting circuit that extracts from an image of an eye of an animal to be identified including a pupil and an irial granule an outline of the pupil; (b) an arc application processing circuit that determines an arc approximate to a specified portion of the extracted outline; (c) an irial granule deforming circuit that deforms the irial granule in the image according to the degree of deformation of the arc up to a reference level; and (d) a storage that registers data on the deformed irial granule of the animal to be registered.
In the preferred mode of the invention, the arc application processing circuit determines the arc in an x-y coordinate system to provide arc data indicating a length, a radius, and an angle of the arc. The irial granule deforming circuit maps the irial granule into polar coordinates wherein a straight line is defined as the reference level based on the arc data.
An irial granule identification circuit is further provided that compares data on the deformed irial granule of the animal to be identified with the data registered in the storage to determine whether the animal is registered or not based on a correlation between the compared data.
According to the second aspect of the present invention, there is provided an animal identification method comprising the steps of: (a) extracting from an image of an eye of an animal to be identified including a pupil and an irial granule an outline of the pupil; (b) applying an approximate arc to a specified portion of the extracted outline; (c) deforming the irial granule in the image according to the degree of deformation of the arc up to a reference level; and (d) registering data on the deformed irial granule of the animal in a storage.
In the preferred mode of the invention, arc data indicating a length, a radius, and an angle of the arc is determined to map the irial granule into polar coordinates wherein a straight line is defined as the reference level based on the arc data.
According to the third aspect of the invention, there is provided an animal eye image processing apparatus designed to process an image of an eye of an animal including a pupil and irial granule comprising: (a) a pupilary rectangle extracting circuit that determines an area in the image showing the smallest gray level of pixels representing the image as an area of the pupil and extracts a rectangular area including the pupilary area; and (b) a pupilary vertical center determining means for projecting a gray level of each pixel in the rectangular area in a horizontal direction to determine an area in the pupilary area showing the smallest frequency as a central position of the pupilary area in a vertical direction.
In the preferred mode of the invention, a pupilary horizontal center determining means is further provided for determining a center between both ends the pupilary area in the horizontal direction as a central position of the pupilary area in the horizontal direction.
According to the fourth aspect of the invention, there is provided an animal eye image processing apparatus designed to process an image of an eye including a pupilary area and an irial granule area in an iris area comprising: (a) a first outline extracting means for determining gray level differences between pixels forming the pupilary area and the irial granule area to extract outlines of both the areas; and (b) a second outline extracting means for determining gray level differences between pixels forming the iris area and the irial granule area to extract outlines of both the areas.
In the preferred mode of the invention, the first outline extracting means includes a pupilary center setting portion that sets a central position of the pupilary area and an outline searching portion that binary-codes an input image with a set threshold value, determines an area whose gray level is lower than the threshold value as an area including at least the central position of the pupilary area, and changes the threshold value to search the outlines of the pupilary area and irial granule area.
An edge image producing means is further provided for detecting an edge of the input image to produce an edge image. The outline searching portion determines whether pixels forming the outlines derived from the binary-coded image binary-coded using the threshold value agree with edge pixels of the edge image.
The pupilary center setting portion projects gray levels of a rectangular area surrounding the pupilary area in a horizontal direction to determine a central position of the pupilary area in a vertical direction using the fact that a pupil has the lowest gray level and defines a central position of the pupilary area in a horizontal direction at a central position of the rectangular area in the horizontal direction.
The second outline extracting means includes a search start point setting portion that sets a search start point position estimated to be within the irial granule area and an outline searching portion that binary-codes an input image with a set threshold value, determines an area whose gray level is lower than the threshold value as an area including at least the search start point, and changes the threshold value to search the outlines of the iris area and irial granule area.
The outline searching portion determines whether pixels forming the outlines derived from the image binary-coded u
Frank Robert J.
Mehta Bhavesh
OKI Electric Industry Co., Ltd.
Venable
Wood Allen
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