Finding a Rational Set of Features for Handwritten Signature Recognition

In this paper we proposed the approach for dynamic handwritten signatures recognition. We proposed a formal model of the handwritten signature, containing fuzzy features of curvature of discrete handwritten signature functions. We proposed handwritten signature reference template creation algorithm, characterized by the use of the potential method for constructing membership functions of fuzzy features. The choice of a rational set of features has been implemented, which allows to minimize the false accept rate (up to 0.05%), as well as a rational set that minimizes the equal error rate (up to 0.36%), which significantly exceeds the efficiency of existing handwritten signature recognition algorithms.