A Minutiae Count Based Method for Fake Fingerprint Detection

Fingerprint based biometric systems are ubiquitous because they are relatively cheaper to install and maintain, while serving as a fairly accurate biometric trait. However, it has been shown in the past that spoofing attacks on many fingerprint scanners are possible using artificial fingerprints generated using, but not limited to gelatin, Play-Doh and Silicone molds. In this paper, we propose a novel method based on the minutiae count for detecting the fake fingerprints generated using these methods. The proposed algorithm has been tested on the standard FVC (Fingerprint Verification Competition) 2000-2006 dataset and the accuracy was reported to be well above 85%. We also present a literature survey of the previous algorithms for fake fingerprint detection.