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Online handwritten signature verification based on the most stable feature and partition

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Abstract

Existing methods for online signature verification are generally writer independent, as a common set of features is used for all writers during verification. In this paper, we propose a new method of online handwritten signature verification. Our approach is based on the writer dependent feature as well as writer dependent partition. The two decisions namely optimal feature suitable for a writer and a partition to be used for authenticating the writer, they are taken based on the error rate at the training phase. It is difficult for the forger to imitate the shape and dynamic characteristics of the signer at the same time. According to this feature, we propose to decompose signature trajectories depending upon pressure, velocity direction angle, and velocity information and perform verification on the most stable partition. Experimental results demonstrate superiority of our approach in online signature verification in comparison with other schemes.

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Acknowledgements

We would like to thanks the anonymous reviewers for their careful reading and useful comments. This work was supported by the National Natural Science Foundation of China (U1405255, 61671360, 61672415, 61672409), and the Fundamental Research Funds for the Central Universities (JB161505).

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Authors and Affiliations

  1. School of Computer Science and Technology, Xidian University, Xi’an, 710071, China

    Li Yang & Xiaoyan Jin

  2. School of Cyber Engineering, Xidian University, Xi’an, 710071, China

    Qi Jiang

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  1. Li Yang
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  2. Xiaoyan Jin
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  3. Qi Jiang
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Correspondence to Li Yang.

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Yang, L., Jin, X. & Jiang, Q. Online handwritten signature verification based on the most stable feature and partition. Cluster Comput 22 (Suppl 1), 1691–1701 (2019). https://doi.org/10.1007/s10586-018-1749-3

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