Application of hidden Markov models for signature verification

Abstract

This paper describes a technique for on-line signature verification using Hidden Markov Models (HMMs). Signatures are captured and digitized in real-time using a graphic tablet. For each signature a HMM is constructed using a set of sample signatures described by the normalized directional angle function of the distance along the signature trajectory. The Baum-Welch algorithm is used for both training and classification. Experimental results based on 496 signatures from 31 subjects are presented which show that HMM technique is very potential for signature verification.