Off-line Signature Verification Using Neural Network
Ashwini Pansare, Shalini Bhatia · 2012
Abstract — a number of biometric techniques have been proposed for personal identification in the past. Among the vision-based ones are face recognition, fingerprint recognition, iris scanning and retina scanning. Voice recognition or signature verification are the most w idely known among the nonvision based ones.As signatures continue ti play an important role in financial, commercial and legal transactions, truly secured authentication becomes more and more crucial. A signature by an authorized person is considered to be the “seal of approval ” and remains the most pr eferred means of authentication.The method presented in this paper consists of image prepossessing, geometric feature extraction, neural network training with extracted features and verifcation. A verification stage includes applying the extracted features of test signature to a trained neural network which w ill classify it as a genuine or forged.