Signature Verification Using Morphological Features Based on Artificial Neural Network

For identification of a particular human being signatures prove to be an important biometric. The signature of a person is an important biometric attribute of a human being which can be used to authenticate human identity. However human signatures can be handled as an image and recognized using computer vision and neural network techniques. With modern computers, there is need to develop fast algorithms for signature recognition. There are various approaches to signature recognition with a lot of scope of research. In this paper, off-line signature recognition & verification using neural network is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified cbn based on parameters extracted from the signature using various image processing techniques. This paper presents a proposed method for verifying offline-signatures .Novel features are used for classification of signatures. A Feed Forward Neural Network will be used for verifying signatures and to determine its accuracy.