A fuzzy framework for offline signature verification

Signature verification is a highly complex and challenging task. This paper presents a similarity measure based person-dependent off-line signature verification using fuzzy techniques in image contrast enhancement, feature extraction and verification. Two sets of experimental studies are conducted on CEDAR benchmark dataset and the results are reported. First, experiments are conducted on the signature images where the features extracted using gray level intensity, are characterized by interval-valued fuzzy sets and classified as genuine or forgery, using a similarity score. Then, signature images are contrast intensified using fuzzy sets / intuitionistic fuzzy sets and verified as above. Experimental results show that the application of fuzzy techniques in image enhancement, feature extraction and verification are more promising than techniques available in the literature in terms of classification accuracy and time.