Title: Classification of fingerprint images to real vs. spoof

Authors: Tatiana Barsky; Ariel Tankus; Yehezkel Yeshurun

Addresses: School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel. ' Department of Biomedical Engineering Technion – Israel Institute of Technology, Haifa 32000, Israel. ' School of Computer Science, Tel-Aviv University, Tel-Aviv 69978, Israel

Abstract: Biometric identification is becoming a leading technology for identity management and security systems. Nonetheless, the use of counterfeit elastic fingerprints (|spoofing|) may break these measures. In this paper, we address the problem of fingerprint spoofing based solely on image features extracted from 2D fingerprint images. By combining several low-accuracy methods, a robust high-performance classifier for real vs. fake fingerprint images is constructed. Its high accuracy is demonstrated on a large fingerprint database. The method thus shows high potential for improving existing fingerprint authentication devices.

Keywords: ?ngerprint images; anti-spoo?ng; anti-faking; ACL; anti-counterfeit layer; fingerprint authentication; biometric identi?cation; identity theft; feature extraction; image classification; fingerprint classi?cation; combination of algorithms; biometrics; fingerprint spoofing.

DOI: 10.1504/IJBM.2012.044289

International Journal of Biometrics, 2012 Vol.4 No.1, pp.1 - 21

Received: 29 Sep 2010
Accepted: 23 Feb 2011
Published online: 29 Nov 2014 *

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