Abstract
The signature verification is the behavioral parameter of biometrics and is used to authenticate a person. A typical signature verification system generally consists of four components: data acquisition, preprocessing, feature extraction and verification. In this paper, Biometric Security System Based on Signature Verification Using Neural Networks (BSSV) is presented. The global and grid features are combined to generate new set of features for the verification of signature. The Neural Network 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 algorithms.
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