# US 10,121,054 B2 · Systems and methods for improving spoof detection based on matcher alignment information > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,121,054 B2 - Document ID: US10121054B2 - Status: Granted - Kind: B2 - Application number: 15/388,908 - Filed: 2016-12-22 - Published: 2018-05-10 - Granted: 2018-11-06 - Earliest claimed: 2016-11-10 - Assignees: Synaptics Incorporated - Applicants: Synaptics Incorporated - Inventors: Rohini Krishnapura; Anthony P. Russo - Web page: https://patentgrep.com/patent/US10121054B2 ## CPC - G06V 40/1365: {Matching; Classification} - G06V 40/40: Spoof detection, e.g. liveness detection - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract 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. ## Claims ### Claim 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. ### Claim 2 (depends on 1) 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. ### Claim 3 (depends on 1) 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. ### Claim 4 (depends on 1) 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. ### Claim 5 (depends on 1) 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. ### Claim 6 (depends on 1) 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. ### Claim 7 (depends on 6) The electronic device of claim 6, wherein the second weight is greater than the first weight. ### Claim 8 (depends on 1) 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. ### Claim 9 (depends on 1) 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. ### Claim 10 (depends on 1) 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. ### Claim 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. ### Claim 12 (depends on 11) 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. ### Claim 13 (depends on 11) 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. ### Claim 14 (depends on 11) 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. ### Claim 15 (depends on 11) 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. ### Claim 16 (depends on 11) 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. ### Claim 17 (depends on 16) The method of claim 16, wherein the second weight is greater than the first weight. ### Claim 18 (depends on 11) 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. ### Claim 19 (depends on 11) 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. ### Claim 20 (depends on 11) 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. ### Claim 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. ### Claim 22 (depends on 21) 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.