Applying dynamic methods in off-line signature recognition

Juan Jose Igarza; Inmaculada Hernaez; Inaki Goirizelaia; Koldo Espinosa

doi:10.1117/12.540421

25 August 2004 Applying dynamic methods in off-line signature recognition

Juan Jose Igarza, Inmaculada Hernaez, Inaki Goirizelaia, Koldo Espinosa

Proceedings Volume 5404, Biometric Technology for Human Identification; (2004) https://doi.org/10.1117/12.540421
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

In this paper we present the work developed on off-line signature verification using Hidden Markov Models (HMM). HMM is a well-known technique used by other biometric features, for instance, in speaker recognition and dynamic or on-line signature verification. Our goal here is to extend Left-to-Right (LR)-HMM to the field of static or off-line signature processing using results provided by image connectivity analysis. The chain encoding of perimeter points for each blob obtained by this analysis is an ordered set of points in the space, clockwise around the perimeter of the blob. We discuss two different ways of generating the models depending on the way the blobs obtained from the connectivity analysis are ordered. In the first proposed method, blobs are ordered according to their perimeter length. In the second proposal, blobs are ordered in their natural reading order, i.e. from the top to the bottom and left to right. Finally, two LR-HMM models are trained using the parameters obtained by the mentioned techniques. Verification results of the two techniques are compared and some improvements are proposed.

Citation Download Citation

Juan Jose Igarza, Inmaculada Hernaez, Inaki Goirizelaia, and Koldo Espinosa "Applying dynamic methods in off-line signature recognition", Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); https://doi.org/10.1117/12.540421

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