Analysis of Intra-Person Variability of Features for Off-line Signature Verification

Abstract:- One of the major challenges in off-line signature verification is the fact that a person’s own signature is influenced by a number of external and internal factors. This influence results in a high variability even between signatures written by the same signer. This paper proposes a method which is able to model the intra-person variability of a signature feature and also to identify and eliminate the effects of external factors. To demonstrate the efficiency of the algorithm, a sample signature verifier is constructed and evaluated on the Signature Verification Competition 2004 database. Experiments have shown that by using 3 features (endings, loops and skew vectors) an average error rate of 12 % can be achieved by the system. These results may be further improved by increasing the number of features, used during the comparison of signatures. Key-Words:- signature verification; off-line; classification, normal distribution