Fusion of multiple fingerprint matchers by single-layer perceptron with class-separation loss function

  • Authors:

  • Gian Luca Marcialis;Fabio Roli

  • Affiliations:

  • Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d'Armi, 09123 Cagliari, Italy;Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d'Armi, 09123 Cagliari, Italy

  • Venue:
  • Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
  • Year:
  • 2005

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Abstract

In this paper, a perceptron-based algorithm for fusion of multiple fingerprint matchers is presented. The person to be identified submits to the personal authentication system her/his fingerprint and claimed identity. Multiple fingerprint matchers provide a set of verification scores, that are then fused by a single-layer perceptron with class-separation loss function. Weights of such perceptron are explicitly optimised to increase the separation between genuine users and impostors (i.e., unauthorized users). Reported experiments show that such modified perceptron allows improving the performances and the robustness of the best individual fingerprint matcher, and outperforming some commonly used fusion rules.