A Theoretical and Experimental Analysis of Template Co-update in Biometric Verification Systems

  • Luca Didaci
  • Gian Luca Marcialis
  • Fabio Roli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)

Abstract

Template update in biometric recognition system is aimed to improve the representativeness of available templates in order to make them adaptive to the large intra-class variations characterizing biometrics (e.g. fingerprints and faces). Among others, semi-supervised approaches to template update have been recently proposed. Since the lack of representativeness is due to the impossibility of sampling all possible variations of a given client biometric, these approaches exploit samples submitted during the recognition phase by adding the “highly genuine” ones to the related client gallery. In particular, the template co-update algorithm, which uses the mutual help of two complementary biometric matchers, has shown promising experimental results. However, no theoretical model has been proposed to explain the behaviour of the co-update algorithm and support the experimental results. This is the goal of this paper. Experimental results show the correctness of the proposed theoretical model.

Keywords

Face Recognition Biometric System Fingerprint Image Face Matcher Fingerprint Matcher 
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 2008

Authors and Affiliations

  • Luca Didaci
    • 1
  • Gian Luca Marcialis
    • 2
  • Fabio Roli
    • 2
  1. 1.Department of Pedagogical and Philosophical SciencesUniversity of CagliariItaly
  2. 2.Department of Electrical and Electronic Engineering, Piazza d’ArmiUniversity of Cagliari, ItalyCagliariItaly

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