Online Signature Verification Using Energy, Angle and Directional Gradient Feature With Neural Network
Priyank Jain1 and Jayesh Gangrade2
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Signature used as a biometric is implemented in various systems as well as every signature signed by each person is distinct at the same time. It is very important to have anonline computerized signature Verification system differentiate digital signature. Hand written signature used every day at various places (Bank, Office etc) for the authentication of a person, but a signature of a person may not be same at different time or it may be generated by some fraud way. So therobust system is required for verification of the signature. The signature verification can be done either online or offline, here we are using online signature verification network. In the proposed system the signatures is taking as a image by the signature pad and apply image processing technique before the feature extraction to make the system effective. The angle, energy and chain code features are used in this paper to differentiate the signature. Neural network is used as a classifier for this system. The studies of online signature verification are given in this paper.