Off-line Chinese Handwriting Signature Verification Based on Different Kinds of Features and Classifiers

For the problem of off-line Chinese handwriting signature verification,this paper presents a methodology of integrated identification based on different kinds of features and classifiers.In this system,three kinds of features are extracted from the signature images and classified by their single BP ANN(Artificial neural network).Compared with single feature or classifier,the proposed algorithms in our system are proved to be more effective.