Off-line Signature Verification based on Angular Features

Signature is widely used as a means of personal verification which emphasizes the need for a signature verification system. In this paper, Off-line Signature Verification based on Angular Features (OSVAF) is proposed. The scanned signature image is skeletonized and exact signature area is obtained by preprocessing. In the first phase, the signature is divided into 128 blocks using the center of signature by counting the number of black pixels and the angular feature in each block is determined to generate 128 angular features. In the second phase the signature is divided into 40 blocks from each of the four corners of the signature to generate 40 angular features. Totally 168 angular features are considered from phase one and two to verify the signature. The difference between the angular features of the genuine and test signatures is computed and compared with the threshold value to authenticate the signature. It is observed that the proposed algorithm has better FAR, FRR and EER compared to the existing algorithms.