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Offline Signature Verification Based on SVM and Neural Network

Anjali.R, Manju Rani Mathew

Biometrics plays a significant role in day to day life. It is widely used as a means of personal identification and authentication. Of this signature is most important. Handwritten signature is unique to an individual and virtually impossible to duplicate. This emphasizes the need for an automatic verification system. The aim of this paper is to measure gray level features of an image when it is distorted by a complex background and train by using neural network classifier and SVM. The practical signature verification problems include problems due to the need of segmenting the signature from the image document. This problem is overcome in this paper by calculating the gray level distortion and segmenting the original signature from the complex backgrounds. Then the image is trained by a neural network by using feed forward back propagation algorithm and SVM