Perceptron-based fusion of multiple fingerprint matchers

TitlePerceptron-based fusion of multiple fingerprint matchers
Publication TypeConference Paper
Year of Publication2003
AuthorsMarcialis, GL, Roli, F
EditorM. Marinai, G;S
Conference NameFirst International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR03)
Pagination92-99
Date Published12/09/2003
Conference LocationFirenze (Italy)
ISBN Number88-7957-221-0
Keywordsbio02, biometrics
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 perceptron-based 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.

Citation Key 180