On-Line Signature Verification Using Hidden Markov Models with Number of States Estimation from the Signature Duration

Abstract

In this paper we present a novel HMM-based automatic signature verification system where the number of states is estimated from the duration of the signatures. This structural user-dependent approach has allowed to obtain high verification rates with a small number of enrolment samples and using only the two basic local x-y geometric features plus their first time derivatives. The proposed system has been tested with the MCYT database reporting EERs of 2.09% with random forgeries and 6.14% with skilled forgeries using only three signatures for enrolment.