Classification of fingerprint images to real vs. spoof

Tatiana Barsky, Ariel Tankus, Yehezkel Yeshurun

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalInternational Journal of Biometrics
Volume4
Issue number1
DOIs
StatePublished - 2012

Keywords

  • ACL
  • Anti-counterfeit layer
  • Anti-faking
  • Anti-spoofing
  • Authentication
  • Biometric identification
  • Classification
  • Combination of algorithms
  • Feature extraction
  • Fingerprint
  • Identity theft

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