Hand-based biometric analysis
First Claim
1. A method of determining identity using a computing system that implements a biometric analysis tool, the method comprising:
- with the computing system that implements the biometric analysis tool, performing biometric analysis on an image of a hand to produce plural feature parameters without requiring a particular orientation of the hand during image capture or for the biometric analysis, wherein the biometric analysis includes;
determining a silhouette representation from the image of the hand;
segmenting the silhouette representation into plural segment images representing palm and plural fingers of the hand without using landmark points during the segmenting, the plural fingers including a thumb, wherein the palm is segmented from the thumb;
determining the plural feature parameters from the plural segment images, respectively, each of the plural feature parameters indicating geometry of a different part among the palm and the plural fingers of the hand; and
making an identity decision based at least in part on the plural feature parameters and stored descriptors representing one or more previously-analyzed hand images, wherein a different weight is associated with each of the plural feature parameters, respectively.
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Abstract
Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.
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Citations
38 Claims
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1. A method of determining identity using a computing system that implements a biometric analysis tool, the method comprising:
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with the computing system that implements the biometric analysis tool, performing biometric analysis on an image of a hand to produce plural feature parameters without requiring a particular orientation of the hand during image capture or for the biometric analysis, wherein the biometric analysis includes; determining a silhouette representation from the image of the hand; segmenting the silhouette representation into plural segment images representing palm and plural fingers of the hand without using landmark points during the segmenting, the plural fingers including a thumb, wherein the palm is segmented from the thumb; determining the plural feature parameters from the plural segment images, respectively, each of the plural feature parameters indicating geometry of a different part among the palm and the plural fingers of the hand; and making an identity decision based at least in part on the plural feature parameters and stored descriptors representing one or more previously-analyzed hand images, wherein a different weight is associated with each of the plural feature parameters, respectively. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A method comprising:
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with a computing system that implements a biometric analysis tool, performing biometric analysis on an image of a hand to produce plural Zernike moment values, wherein the biometric analysis includes; determining a silhouette representation from the image of the hand; and using the silhouette representation to determine the plural Zernike moment values, the plural Zernike moment values indicating geometry of the hand, including; storing plural common terms; and reusing the stored terms, thereby reducing overall computational complexity; and making an identity decision based at least in part on the plural Zernike moment values and stored descriptors representing one or more previously-analyzed hand images. - View Dependent Claims (24, 25)
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26. A computing system that implements a biometric analysis tool, the computing system including:
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a processing unit; and memory storing computer-executable instructions for causing the computing system to perform a method comprising; performing biometric analysis on an image of a hand to produce plural Zernike moment values, wherein the biometric analysis includes; determining a silhouette representation from the image of the hand; and using the silhouette representation to determine the plural Zernike moment values, the plural Zernike moment values indicating geometry of the hand, including; storing plural common terms; and reusing the stored terms, thereby reducing overall computational complexity; and making an identity decision based at least in part on the plural Zernike moment values and stored descriptors representing one or more previously-analyzed hand images. - View Dependent Claims (27, 28)
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29. A computing system that implements a biometric analysis tool, the computing system including:
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a processing unit; and memory storing computer-executable instructions for causing the computing system to perform a method comprising; performing biometric analysis on an image of a hand to produce plural feature parameters without requiring a particular orientation of the hand, wherein the biometric analysis includes; determining a silhouette representation from the image of the hand; segmenting the silhouette representation into plural segment images representing palm and plural fingers of the hand without using landmark points during the segmenting, the plural fingers including a thumb, wherein the palm is segmented from the thumb; and determining the plural feature parameters from the plural segment images, respectively, each of the plural feature parameters indicating geometry of a different part among palm and plural fingers of the hand; and making an identity decision based at least in part on the plural feature parameters and stored descriptors representing one or more previously-analyzed hand images, wherein a different weight is associated with each of the plural feature parameters, respectively. - View Dependent Claims (30, 31, 32, 33)
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34. A computing system that implements a biometric analysis tool, the computing system including:
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a processing unit; and memory storing computer-executable instructions for causing the computing system to perform a method comprising; performing biometric analysis on an image of a hand to produce plural feature parameters without requiring a particular orientation of the hand during image capture or for the biometric analysis, wherein the biometric analysis includes; determining a silhouette representation from the image of the hand; segmenting the silhouette representation, including; filtering out plural fingers of the hand from the silhouette representation to identify a segment image for a palm of the hand, wherein the filtering out the plural fingers uses morphological closing operations; removing the palm from the silhouette representation to identify segment images for the plural fingers, respectively; and determining the plural feature parameters from the segment image for the palm and the segment images for the plural fingers, respectively, each of the plural feature parameters indicating geometry of a different part among the palm and the plural fingers of the hand; and making an identity decision based at least in part on the plural feature parameters and stored descriptors representing one or more previously-analyzed hand images, wherein a different weight is associated with each of the plural feature parameters, respectively. - View Dependent Claims (35, 36, 37)
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38. A computing system that implements a biometric analysis tool, the computing system including:
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a processing unit; and memory storing computer-executable instructions for causing the computing system to perform a method comprising; performing biometric analysis on an image of a hand to produce plural feature parameters without requiring a particular orientation of the hand during image capture or for the biometric analysis, wherein the image further includes part of a forearm, and wherein the biometric analysis includes; determining a silhouette representation from the image of the hand, wherein the silhouette representation further represents the part of the forearm; segmenting the silhouette representation, including; identifying a shape over a palm of the hand inside the silhouette representation; using an intersection between the shape over the palm and the silhouette representation to identify the part of the forearm from the silhouette representation; filtering out plural fingers of the hand from the silhouette representation to identify a segment image for the palm; removing the palm from the silhouette representation to identify segment images for the plural fingers, respectively; and smoothing the segment images for the plural fingers; and determining the plural feature parameters from the segment image for the palm and the segment images for the plural fingers, respectively, each of the plural feature parameters indicating geometry of a different part among the palm and the plural fingers of the hand; and making an identity decision based at least in part on the plural feature parameters and stored descriptors representing one or more previously-analyzed hand images, wherein a different weight is associated with each of the plural feature parameters, respectively.
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Specification