Approach For Off-line Signature Verification Research Articles

Fuzzy Logic Based Adaptive Resonance Theory-1 Approach for Offline Signature Verification

Abstract This paper presents the use fuzzy logic with adaptive resonance theory-1 in signature verification. Fuzzy model is capable of stable learning of recognition categories in response to arbitrary sequences of binary input pattern. The work was carried out on two famous available signature corpuses i.e. MCYT (Online Spanish signatures database) and GPDS (Grupo de Procesado Digital de la se?al). Local binary patterns (LBP) and Gray Level Co-occurrence Matrices (GLCM) features were calculated for robust offline signature verification system. Training and verification was done using fuzzy adaptive resonance theory-1(FART-1). The system is trained and verified for different datasets to increase the accuracy of the classifier. The results thus obtained are robust than other existing techniques. The FAR and FRR for the system is 0.74% and 0.83% respectively.

A Novel Automated Approach for Offline Signature Verification Based on Shape Matrix

The handwritten signature has been the most natural and long lasting authentication scheme in which a person draw some pattern of lines or writes his name in a different style. The signature recognition and verification are a behavioural biometric and is very challenging due to the variation that can occur in person’s signature because of age, illness, and emotional state of the person. As far as the representation of the signature is concerned a classical technique of thinning or skeleton is mostly used. In this paper, we proposed a new methodology for signature verification that uses structural information and original strokes instead of skeleton or thinned version to analyse the signature and verify. The approach is based on sketching a fixed size grid over the signatures and getting 2-Dimensional unique templates which are then compared and matched to verify a query signature as genuine or forged. To compute the similarity score between two signature’s grids, we follow template matching rule and the Signature grid’s cell are mapped and matched with respect to position. The proposed framework is fast and highly accurate with reduce false acceptance rate and false