Signature classification using optimum contour

Authors:
J. Francisco Vargas;Carlos M. Travieso;Miguel A. Ferrer;Jesus B. Alonso
Affiliations:
Department of Signals and Communications, Universidad de Las Palmas de Gran Canaria, Spain and Department of Electronic Engineering, Universidad de Antioquia, Colombia;Department of Signals and Communications, Universidad de Las Palmas de Gran Canaria, Spain;Department of Signals and Communications, Universidad de Las Palmas de Gran Canaria, Spain;Department of Signals and Communications, Universidad de Las Palmas de Gran Canaria, Spain
Venue:
ACS'06 Proceedings of the 6th WSEAS international conference on Applied computer science
Year:
2006

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Abstract

An offline handwritten signature classification approach is presented. The signature is parameterized using the radius values for contour points in the polar coordinates space. In order to determine the optimum outline for the classification task, nearest and faraway points were took into account. HMM and SVMLight model are analyzed in this work. Selecting faraway points offers better results, and using SVMLight model with polynomial kernel presents the best accuracy values obtained (99,02%).