New method for the on-line signature verification based on horizontal partitioning

• We propose new algorithm to the dynamic signature verification using partitioning.
• Our algorithm takes advantage of a flexible neuro-fuzzy classifier.
• Our algorithm takes into account hierarchy of partitions individually for each user.
• Work of our method allows to easy interpretation.

Verification of identity based on the analysis of dynamic signatures is an important problem of biometrics. The effectiveness of the verification significantly increases when the dynamic characteristics of signature (e.g. velocity of the pen) are considered. These characteristics are individual for each user and difficult to imitate. The effectiveness of the verification can be further improved by using partitioning. In this paper we propose a new method which uses partitioning. In our method partitions represent areas of high and low speed of signature and high and low pen׳s pressure. All selected partitions are used by our algorithm, but more important in the classification process are these partitions, in which the signatures of the user acquired during training phase are more stable. Moreover, final classification is interpretable. In this paper we present the simulation results of the proposed method for the two databases: SVC2004 and BioSecure Database.