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

Author(s): Bortolozzi, F. | Murshed, N. | Sabourin, R. |

Year: 1995

Citation: Proceedings of the Third International Conference on Document Analysis and Recognition (ICDAR 95), Vol. I, pp. 191-196. Montreal, 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.

Topics: Image Analysis, Applications: Character Recognition, Models: Fuzzy ARTMAP,

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