135 | Page SIGNATURE RECOGNITION AND VERIFICATION USING CASCADING OF TCHEBICHEF MOMENT AND CONTOUR CURVATURE FEATURES IN MATLAB Priyanka Pradhan 1 , Vipul Rastogi 2 , Mohd. Auragzeb Atiq 3 , L.S. Maurya 4 1,2,3 M.Tech Scholar, 4 HOD(CS/IT Deptt.) SRMSCET, Bareilly (India) ABSTRACT Signature verification is most commonly used as an authorization tool from the beginning till now. Many people uses bank cheques for most of their transactions. Although banks are computerized, but still verification process of signature in cheques is done manually which consumes time and even misleads sometimes. Signatures verification process can be done online or off-line depending upon the application. In this paper, model is proposed for the signature verification and testing using the Offline Signature Verification System. The acquired signature from the bank cheque is preprocessed for the purpose of feature extraction. Here tchebichef moment feature and contour curvature features of the signature are extracted and cascaded for increasing accuracy. The extracted features are used to train a multilayer Feed Forward Neural Network. The signature features, to be tested, are fed to the trained neural network to find whether the signature is genuine or a forged one. Keywords: Feature Cascading, Contour Curvature Feature, Tchebichef Moment Based Feature, ANN and Signature Recognition I. INTRODUCTION The need to make sure that only the right people are authorized to access high-security systems has paved the way for the development of systems for automatic personal authentication. Handwritten signature verification has been identified as a main contender in the search for a secure personal verification system. Signatures in offline systems are based on the scanned image of the signature and verification of signature is based on extracted features of signature. Here multi-features will be used for the process of feature extraction of signature from the preprocessed scanned image of a signature. Here two methods were used for the process of feature extraction of signature from the preprocessed scanned image of a signature. One of the method is moment based method. Many moment based methods are used for extracting feature of a signature but we have used tchebichef moment feature. The second method is based on contour curvature. Contour is very important boundary feature used for finding similarity between shapes. The objective of this paper is to emphasize the importance of the use of biometrics in the area of secure person authentication. In this paper the efficiency of these features for signature Recognition is studied. This provides a biometrics accuracy as a highest level of network security with the fusion of multiple feature extraction. Based