Paper Title
Offline Handwritten Signature Verification Using Template Matching And Clustering Technique

Handwritten signatures are very important in our social and legal life for verification and authentication. A signature can be a "seal of approval" only if it is done by an authorized person which is a full proof way of authentication. Even two signatures of same person can have some kind of differences that is they cannot have perfect resemblances. Their positions may vary with respect to start and finish. Also, the angle of inclination of the signatures, space between each letter, height of each letter, all vary even with the same person. For comparison, it becomes a challenging task for two signatures to be of same person. In this paper, we presented the method that consists of image pre-processing, feature extraction, template matching and clustering technique and hamming distance verification.