Static signature verification employing a kosko-neuro-fuzzy approach

Abstract

To overcome difficulties in transferring “classical” handwriting examination methods into computer algorithms ahybrid neuronal system, proposed by Kosko [1], was employed to derive rules for signature region matching. The segmentation of signatures, written on paper documents, into regions will be presented and the two stage fuzzy rule learning, for finding and tuning the fuzzy rules will be discussed. By using the neuro-fuzzy approach [1] a region matching performance of 98% was achieved. © Springer-Verlag Berlin Heidelberg 2002.