Classification of fingerprint images to real vs. spoof

  • Authors:
  • Tatiana Barsky;Ariel Tankus;Yehezkel Yeshurun

  • Affiliations:
  • 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

  • Venue:
  • International Journal of Biometrics
  • Year:
  • 2012

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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.