Iris deblurring method based on global and local iris image statistics
First Claim
Patent Images
1. A method of identifying a living being, comprising the steps of:
- using a camera to capture a blurred visual image of an iris of the living being;
digitally unblurring the blurred visual image based on a distribution of eye image gradients in an empirically-collected sample of eye images and distributions from characteristics of local regions;
processing the unblurred image to determine an identity of the living being; and
approximating the distribution of eye image gradients as a quadratic piecewise function.
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Abstract
A method of identifying a living being includes using a camera to capture a blurred visual image of an iris of the living being. The blurred visual image is digitally unblurred based on a distribution of eye image gradients in an empirically-collected sample of eye images and characteristics of pupil region. The unblurred image is processed to determine an identity of the living being.
11 Citations
17 Claims
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1. A method of identifying a living being, comprising the steps of:
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using a camera to capture a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on a distribution of eye image gradients in an empirically-collected sample of eye images and distributions from characteristics of local regions; processing the unblurred image to determine an identity of the living being; and approximating the distribution of eye image gradients as a quadratic piecewise function. - View Dependent Claims (2, 3)
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4. A method of identifying a living being, comprising the steps of:
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using a camera to capture a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on a distribution of eye image gradients in an empirically-collected sample of eye images and distributions from characteristics of local regions; processing the unblurred image to determine an identity of the living being; and forming the distribution of eye image gradients from statistics derived from measurements of a population of eye regions.
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5. A method of identifying a living being, comprising the steps of:
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using a camera to capture a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on a distribution of eye image gradients in an empirically-collected sample of eye images and distributions from characteristics of local regions; processing the unblurred image to determine an identity of the living being; forming the distributions from characteristics of local regions from characteristics of intensity value of pupil region; and forming the distribution of eye image gradients from global intensity value statistics derived from measurements of a population of eye regions. - View Dependent Claims (6, 7)
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8. A method of identifying a living being, comprising the steps of:
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using a camera to capture a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on; distributions from intensity value of pupil region; and distribution from global intensity value statistics derived from measurements of a population of eye regions; processing the unblurred image to determine an identity of the living being; and modeling the global intensity value statistics as a quadratic piecewise function. - View Dependent Claims (9, 10)
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11. A method of identifying a living being, comprising the steps of:
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using a camera to capture a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on; distributions from intensity value of pupil region; and distribution from global intensity value statistics derived from measurements of a population of eye regions; and processing the unblurred image to determine an identity of the living being, wherein distributions from characteristics of intensity value of pupil region include; distribution from local highlight intensity value of pupil region; and distribution from local non-highlight intensity value of pupil region. - View Dependent Claims (12)
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13. A method of identifying a living being, comprising the steps of:
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capturing a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on; distribution from local highlight intensity value of pupil region; distribution from local non-highlight intensity value of pupil region; and distribution of global intensity value statistics derived from measurements of a population of eye regions; processing the unblurred image to determine an identity of the living being; and modeling the global intensity value statistics as a quadratic piecewise function. - View Dependent Claims (14, 15, 16)
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17. A method of identifying a living being, comprising the steps of:
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capturing a blurred visual image of an iris of the living being; digitally unblurring the blurred visual image based on; distribution from local highlight intensity value of pupil region; distribution from local non-highlight intensity value ofpupil region; and distribution of global intensity value statistics derived from measurements of a population of eye regions; processing the unblurred image to determine an identity of the living being; detecting the highlight regions and the non-highlight regions around pupil region in a captured image; deriving the distribution of the local highlight intensity value from the portion identified as corresponding to the highlight regions; and deriving the distribution of the local non-highlight highlight intensity value from the portion identified as corresponding to the non-highlight regions.
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Specification