Combining local, regional and global matchers for a template protected on-line signature verification system
In this work an on-line signature authentication system based on an ensemble of local, regional, and global matchers is presented. Specifically, the following matching approaches are taken into account: the fusion of two local methods employing Dynamic Time Warping, a Hidden Markov Model based approach where each signature is described by means of its regional properties, and a Linear Programming Descriptor classifier trained by global features. Moreover, a template protection scheme employing the BioHashing and the BioConvolving approaches, two well known template protection techniques for biometric recognition, is discussed. The reported experimental results, evaluated on the public MCYT signature database, show that our best ensemble obtains an impressive Equal Error Rate of 3%, when only five genuine signatures are acquired for each user during enrollment. Moreover, when the proposed protected system is taken into account, the Equal Error Rate achieved in the worst case scenario, that is,when an impostor is able to steal the hash keys, is equal to 4.51%, whereas an Equal Error Rate ?0 can be obtained when nobody steals the hash keys.
template protection on-line signature dynamic time warping hidden markov models linear programming descriptor biohashing ensemble of classifiers