Offline Signature Verification Using Artificial Neural Network

This review paper off-line signature verification and recognition using a new approach that depends on a artificial neural network which discriminate between two classes (i) forgery and (ii) original signature. The proposed scheme is based on the technique that applies pre-processing on the signature, feature point extraction and neural network training and finally verifies the authenticity of the signature. The objective of the proposed scheme is to reduce two vital parameters False Acceptance Rate (FAR) and False Rejection Rate (FRR). That means results are expressed in terms of FAR and FRR and subsequently comparative analysis has been made with existing techniques. The Proposed technique will give more efficient result than most of the existing techniques. Keywords— Off-line Signature, Forgeries, Feature extraction, Neural network, FAR (False Acceptance Rate), FRR (False Rejection Rate).