Paper Title
Offline Signature Verification And Recognition Using Ann

Due to Compare to biometric and cryptographic forms of identification handwritten signatures are considered as the most reliable methods of authenticating a persons identity.To improve security in different transactions like financial, commercial and legal signature plays an important role. This paper presents a method for verifying handwritten offline signatures by using NN, Various features are extracted and used to train the neural network. Keywords—Dynamic Time wrapping, Hidden Markov Models, Neural Networks, Support Vector Machines, Statistical approach, Template matching