On-line Signature Verification Using Segment-to-Segment Graph Matching

This paper proposes a novel approach of on-line signature verification. Firstly, on-line signatures are partitioned into a series of segments, which are then represented by graphs. Four segmentation methods are taken into account. Secondly, graph matching techniques are adopted to compute edit distance between corresponding graphs, which measures the similarity of them. Finally, having been able to compare two signatures, limited genuine signatures are used to train user dependent classifiers for each user. Experiments are conducted to validate the effectiveness of the proposed method and promising results are achieved.