OFF-LINE SIGNATURE VERIFICATION AND RECOGNITION BY SUPPORT VECTOR MACHINE (WedPmPO2)

Author(s) : Emre Ozgunduz (Yildiz Technical University, Turkey) Tulin Senturk (Yildiz Technical University, Turkey) Elif Karsligil (Yildiz Technical University, Turkey)

Abstract : In this paper we present an off-line signature verification and recognition system using the global, directional and grid features of signatures. Support Vector Machine(SVM) was used to verify and classify the signatures and a classification ratio of 0.95 was obtained. As the recognition of signatures represent a multiclass problem SVM's one-against-all method was used. We also compare our methods performance with Artifical Neural Network’s(ANN) backpropagation method

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