On-line Signature Verification Using Graph Representation

This paper proposes a novel approach of on-line signature verification. Firstly, on-line signatures are represented by a series of graphs, whose nodes and edges describe certain properties at sample points and relationship between points respectively. Then, graph matching techniques are introduced to compute edit distance between graphs, which measures the similarity of graphs. Finally, having been able to compare any two signatures through the last two steps, user-dependent classifiers are trained using limited genuine signatures. The proposed method is tested on SUSIG online signature database and shows promising performance.