Off-Line signature verification, without a priori knowledge of class 02.A new approach

Off-Line signature verification, without a priori knowledge of class 02.A new approach

Murshed, Nabeel A. and Bortolozzi, Flavio and Sabourin, Robert

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR 1995

Abstract : This work proposes a new approach to signature verification. It is inspired by the human learning and the approach adopted by the expert examiner of signatures, in which an a priori knowledge of the class of forgeries is not required in order to perform the verification task. Based on this approach, we present a Fuzzy ARTMAP based system for the elimination of random forgeries. Compared to the conventional systems proposed thus far, the presented system is trained with genuine signatures only. Six experiments have been performed on a data base of 200 signatures taken from five writers (40 signatures/writer). Evaluation of the system was measured using different numbers of training signatures (3, 6, 9, 12, 15 and 18).