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In this paper, we propose a novel probabilistic graphical model to address the off-line signature verification problem. Different from previous work, our approach introduces the concept of feature roles according to their distribution in genuine and forgery signatures, with all these features represented by a unique graphical model. And we propose several new techniques to improve the performance of the new signature verification system. Results based on 200 persons' signatures (16000 signature samples) indicate that the proposed method outperforms other popular techniques for off-line signature verification with a great improvement.