Letters: Experimental comparison of one-class classifiers for online signature verification

Authors:
Loris Nanni
Affiliations:
DEIS, IEIIT-CNR, Universití di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
Venue:
Neurocomputing
Year:
2006

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Abstract

Online signature verification systems based on one-class classifiers are presented. Global information is extracted with a feature-based representation and recognized by using an ensemble of one-class classifiers. Experimental results obtained on the SUBCORPUS-100 MCYT signature database (100 signers, 5000 signatures) show that the machine experts, here proposed, outperform the state-of-the-art works both for random and skilled forgeries.