Abstract In this paper, a neural fusion rule for fingerprint verification is presented. The person to be identified submits to the system her/his fingerprint and her/his identity. Multiple fingerprint matchers provide a set of verification scores, that are then fused by a perceptronbased method. The weights of such perceptron are explicitly optimised to increase the separation between genuine users and impostors (i.e., unknown users). To this end, the perceptron learning algorithm was modified. Reported experiments show that such modified perceptron allows improving the performances and the robustness of the best individual fingerprint matcher, and outperforming some simple fusion rules.

Perceptron-based fusion of multiple fingerprint matchers

MARCIALIS, GIAN LUCA;ROLI, FABIO
2003-01-01

Abstract

Abstract In this paper, a neural fusion rule for fingerprint verification is presented. The person to be identified submits to the system her/his fingerprint and her/his identity. Multiple fingerprint matchers provide a set of verification scores, that are then fused by a perceptronbased method. The weights of such perceptron are explicitly optimised to increase the separation between genuine users and impostors (i.e., unknown users). To this end, the perceptron learning algorithm was modified. Reported experiments show that such modified perceptron allows improving the performances and the robustness of the best individual fingerprint matcher, and outperforming some simple fusion rules.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/106871
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact