Abstract
In this paper we proposed the approach for recognition handwritten signatures based on dynamics characteristics and fuzzy sets theory. We suggested the formal model of human handwritten signature, which contains several fuzzy features. We also suggested handwritten signature reference template creation and handwritten signature recognition algorithms. Suggested formal model was used as a basis. Method of potentials was used to obtain membership functions of fuzzy features which makes it possible to create a reference template even under conditions of a small capacity of training set. The research was conducted on the MCYT_Signature_100 signature collection which includes 2500 genuine signatures and 2500 skillful fakes. Suggested approach makes it possible to recognize handwritten signatures even in case of their fuzzy character. Accuracy evaluation results showed FAR value 2.8%, FRR value 0.4% for random fake patterns and FRR value 0.8% for skillful fake patterns, which is better than evaluation results of many others approaches.
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Anisimova, E.S., Anikin, I.V. (2021). Fuzzy Sets Theory Approach for Recognition Handwritten Signatures. In: Radionov, A.A., Gasiyarov, V.R. (eds) Advances in Automation II. RusAutoCon 2020. Lecture Notes in Electrical Engineering, vol 729. Springer, Cham. https://doi.org/10.1007/978-3-030-71119-1_93
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