Method of and system for enrolling and matching biometric data
US-2016162725-A1 · Jun 9, 2016 · US
US10121054B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10121054-B2 |
| Application number | US-201615388908-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 22, 2016 |
| Priority date | Nov 10, 2016 |
| Publication date | Nov 6, 2018 |
| Grant date | Nov 6, 2018 |
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Disclosed is a system and method for performing spoof detection. The method includes: receiving, by a processor from a biometric sensor, an input image of a biometric; obtaining, by the processor, alignment information that aligns the input image to an enrollment image; determining, by the processor, an overlap region and a non-overlap region of the input image relative to the enrollment image; extracting, by the processor, one or more anti-spoof features from the input image based on one or more of the overlap region and the non-overlap region; and, determining, by the processor, whether the input image is a replica of the biometric based on the one or more anti-spoof features.
Opening claim text (preview).
What is claimed is: 1. An electronic device, comprising: a biometric sensor; and a processor configured to: receive, from the biometric sensor, an input image of a biometric; obtaining alignment information that aligns the input image to an enrollment image of the biometric; determine an overlap region and a non-overlap region of the input image relative to the enrollment image based on the alignment information that aligns the input image to the enrollment image; extract one or more anti-spoof features from the input image based on one or more of the overlap region and the non-overlap region; and determine whether the input image is a replica of the biometric based on the one or more anti-spoof features. 2. The electronic device of claim 1 , wherein the alignment information comprises transformation information that, when applied to the input image, translates and rotates the input image to align the input image with an enrollment image. 3. The electronic device of claim 1 , wherein the alignment information comprises a mask or coordinate information that identifies the overlap region and the non-overlap region. 4. The electronic device of claim 1 , wherein the one or more anti-spoof features comprise at least one of a number of keypoints and a number of minutiae in the non-overlap region. 5. The electronic device of claim 1 , wherein the one or more anti-spoof features comprise at least one of a number of keypoints and a number of minutiae in the overlap region. 6. The electronic device of claim 1 , wherein determining whether the input image is a replica of the biometric is based on applying a first weight to the anti-spoof features from the overlap region and applying a second weight to the anti-spoof features from the non-overlap region. 7. The electronic device of claim 6 , wherein the second weight is greater than the first weight. 8. The electronic device of claim 1 , wherein extracting the one or more anti-spoof features from the input image is based on a differential between anti-spoof features in the overlap region of the input image and anti-spoof features in a corresponding portion of an anti-spoof template. 9. The electronic device of claim 1 , wherein extracting the one or more anti-spoof features from the input image is based on a differential between anti-spoof features in the non-overlap region of the input image and anti-spoof features in a corresponding portion of an anti-spoof template. 10. The electronic device of claim 1 , wherein the biometric comprises a fingerprint of a finger, and the replica comprises a gelatin mold, a graphite mold, or a wood glue mold of the fingerprint of the finger. 11. A method for performing spoof detection, comprising: receiving, by a processor from a biometric sensor, an input image of a biometric; obtaining, by the processor, alignment information that aligns the input image to an enrollment image of the biometric; determining, by the processor, an overlap region and a non-overlap region of the input image relative to the enrollment image based on the alignment information that aligns the input image to the enrollment image; extracting, by the processor, one or more anti-spoof features from the input image based on one or more of the overlap region and the non-overlap region; and determining, by the processor, whether the input image is a replica of the biometric based on the one or more anti-spoof features. 12. The method of claim 11 , wherein the alignment information comprises transformation information that, when applied to the input image, translates and rotates the input image to align the input image with an enrollment image. 13. The method of claim 11 , wherein the alignment information comprises a mask or coordinate information that identifies the overlap region and the non-overlap region. 14. The method of claim 11 , wherein the one or more anti-spoof features comprise at least one of a number of keypoints and a number of minutiae in the non-overlap region. 15. The method of claim 11 , wherein the one or more anti-spoof features comprise at least one of a number of keypoints and a number of minutiae in the overlap region. 16. The method of claim 11 , wherein determining whether the input image is a replica of the biometric is based on applying a first weight to the anti-spoof features from the overlap region and applying a second weight to the anti-spoof features from the non-overlap region. 17. The method of claim 16 , wherein the second weight is greater than the first weight. 18. The method of claim 11 , wherein extracting the one or more anti-spoof features from the input image is based on a differential between anti-spoof features in the overlap region of the input image and anti-spoof features in a corresponding portion of an anti-spoof template. 19. The method of claim 11 , wherein extracting the one or more anti-spoof features from the input image is based on a differential between anti-spoof features in the non-overlap region of the input image and anti-spoof features in a corresponding portion of an anti-spoof template. 20. The method of claim 11 , wherein the biometric comprises a fingerprint of a finger, and the replica comprises a gelatin mold, a graphite mold, or a wood glue mold of the fingerprint of the finger. 21. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, causes a computing device to perform spoof detection, by performing steps comprising: receiving, from a biometric sensor, an input image of a biometric; obtaining alignment information that aligns the input image to an enrollment image of the biometric; determining an overlap region and a non-overlap region of the input image relative to the enrollment image based on the alignment information that aligns the input image to the enrollment image; extracting one or more anti-spoof features from the input image based on one or more of the overlap region and the non-overlap region; and determining whether the input image is a replica of the biometric based on the one or more anti-spoof features. 22. The computer-readable storage medium of claim 21 , wherein obtaining the alignment information that aligns the input image to the enrollment image comprises receiving the alignment information from a matcher module.
Physics · mapped topic
Physics · mapped topic
Spoof detection, e.g. liveness detection · CPC title
Matching; Classification · CPC title
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