A Hybrid Approach for Offline Signature Verification using Artificial Neural Networks

The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. Various complex methodologies in the past have been proposed for signature verification through feature extraction. This paper presents a new hybrid algorithm for signature verification which incorporates feed forward training of parameters derived through feature extraction. It results in a much efficient algorithm which is yet simpler to operate from user’s perspective. The method presented in this paper consists of image prepossessing, geometric feature extraction, neural network training with extracted features and verification. The Off-line Signature Recognition and Verification is implemented using MATLAB. Abbreviations: 1. NN: Neural Network 2. HSV: Handwriting signature verification