Signature data generation method

摘要

In on-line signature identification, it is usually difficult to get enough samples. This paper focuses on the work of generating some new signatures according to only a few samples collected advance. In the generating process, we used the knowledge concluded from the observation of lot's of signatures. The knowledge includes the relationship between the writing speed sequences of skilled signatures with different scales, that is to say: the relationship between speed and scale. The knowledge also includes the relationship between writing speed of adjacent points within a signature, which can be consider as the relationship of speed and local surrounding. By modeling the speed sequence of signature as conditional k-th step Markov chain, the relationship of speed and local surrounding is described as the transition probabilities of the Markov chain. The results of the generated signatures show that the method we proposed is useful. The results also prove that the relations we concluded are steady and can be used directly to signature identification.