Citation: Proceedings of the IEEE - International Conference on Neural Networks (ICNN 95), pp. 2179-2184. Perth, 1995.
Abstract: This work presents a fuzzy ARTMAP based off-line signature verification system. Compared to the conventional systems proposed thus far, the presented system is trained with genuine signatures only. Six experiments have been performed on a database 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)