Abstract
In this paper, combined off-line signature verification using Neural Network (CSVNN) is presented. The global and grid features are combined to generate new set of features for the verification of signature. The Neural Network (NN) is used as a classifier for the authentication of a signature. The performance analysis is verified on random, unskilled and skilled signature forgeries along with genuine signatures. It is observed that FAR and FRR results are improved in the proposed method compared to the existing algorithm.KeywordsSignatureNeural NetworkFARFRRGrid features and Global feature
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