Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409554 | Neurocomputing | 2006 | 5 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Loris Nanni,