Tülin Sentürk

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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 represents a multiclass problem SVM's one-against-all(More)
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