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Fingerprint recognition and matching is a common form of user authentication.While a fingerprint is unique to each individual, authentication is vulnerablewhen an attacker can forge a copy of the fingerprint (spoof). To combat thesespoofed fingerprints, spoof detection and liveness detection algorithms arecurrently being researched as countermeasures to this security vulnerability.This paper introduces a fingerprint anti-spoofing mechanism using machinelearning.

Fingerprint Liveness Detection using Minutiae-Independent Dense Sampling of Local Patches