Realistic synthetic off-line signature generation based on synthetic on-line data

Abstract

A novel method for the generation of synthetic offline signatures is presented. The proposed algorithm follows a two steps scheme: first, the raw synthetic dynamic functions of the synthetic signature are generated; second, several ink and paper models are applied to transform the on-line data to realistic static signatures. The novel approach is validated using four different publicly available databases both real and synthetic. The experimental protocol includes the comparison of both types of signatures in terms of: i) performance evaluation of two competitive and totally different verification systems; and ii) visual appearance according to human observers. The experimental results show the high similarity existing between synthetically generated and humanly produced samples, and the potential of the proposed method for the study of the signature trait.