Online Signature Verification Based on Segment Features and HMM
MENG Ming1,2, WU ZhongCheng1, YU Yong1, GE YunJian1
1.Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 2.Department of Automation, University of Science and Technology of China, Hefei 230027
Abstract Writing forces of signature contain a great many individual characteristics, but in current online handwritten signature verification systems this information is often utilized deficiently because of the limitation of the existing input device. In this paper, an online signature verification algorithm using the shape features and the force features is presented. The dynamic trajectory and the writing force of signature are captured by a novel digital tablet, namely FTablet. Each signature is segmented according to its minimum velocity points. Then a 16dimensional vector of shape and force features is extracted for each segment. The resulting sequence is used for training a HMM to achieve signature verification. The experimental results on our database show that the force feature is more difficult to forge than the shape feature and the combination of the two features can effectively improve the performance. The proposed algorithm has achieved equal error rate (EER) of 3.9%.
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2007, Vol. 20 
