Offline Signature Verification Using Critical Region Matching

Abstract

Signature can be seen as an individual characteristic of a person which if modeled with precision can be used for his/her validation. Automatic signature verification is a technique that saves time and money. The paper is focused on skilled forgery detection. In addition, it also lays emphasis on the extraction of the critical regions which are more prone to mistakes. It follows a graph matching approach, which compares these critical regions, taking care of the inevitable intra-personal variations. The results show significant improvement over other approaches for detecting skilled forgery.