Offline Signature Verification through Biometric Strengthening

The offline signature verification rests on the hypothesis that each writer has similarity among signature samples, with small distortion and scale variability. In this paper we propose a novel method to increase the accuracy in biometric matching which we term biometric strengthening. We reported 1.1% equal error rate (EER) over the independent database on random forgery, while casual forgery on EER 1.2% and lastly skilled forgery on EER 2.1% along the paper. Our experiments show that biometric strengthening reduces the false acceptance rate (FAR) and false rejection rate (FRR) by increasing the disparity between the features of the two persons, which tends to tolerate more intrapersonal variance which can reduce the FRR without increasing the probability of false accepts.