Automatic Signature Stability Analysis and Verification Using Local Features

The purpose of writing this paper is two-fold. First, it presents a novel signature stability analysis based on signature´s local / part-based features. The Speeded Up Local features (SURF) are used for local analysis which give various clues about the potential areas from whom the features should be exclusively considered while performing signature verification. Second, based on the results of the local stability analysis we present a novel signature verification system and evaluate this system on the publicly available dataset of forensic signature verification competition, 4NSigComp2010, which contains genuine, forged, and disguised signatures. The proposed system achieved an EER of 15%, which is considerably very low when compared against all the participants of the said competition. Furthermore, we also compare the proposed system with some of the earlier reported systems on the said data. The proposed system also outperforms these systems.