Iris-Biometric Fuzzy Commitment Schemes under Signal Degradation

  • C. Rathgeb
  • A. Uhl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7340)

Abstract

Low intra-class variability at high inter-class variability is considered a fundamental premise of biometric template protection, i.e. it is believed that biometric traits need to be captured under favorable conditions in order to provide practical recognition rates. In this work the impact of blur and noise to fuzzy commitment schemes is investigated and is compared to the impact observed on the accuracy of the underlying recognition scheme. Iris textures are successively blurred and noised in order to measure the robustness of iris-biometric fuzzy commitment schemes.

Keywords

Signal Degradation Feature Extraction Method False Acceptance Rate False Rejection Rate Biometric Template 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • C. Rathgeb
    • 1
  • A. Uhl
    • 1
  1. 1.Multimedia Signal Processing and Security Lab. Department of Computer SciencesUniversity of SalzburgSalzburgAustria

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