Study on Application of HMM to Online Signature Verification Based on Differences of Matched Segment
Wu Zhong · 2011
An approach of hidden markov model (HMM) to online signature verification is proposed, which uses difference values obtained by segmentation dynamic time wrapping (DTW) as observations of model. Firstly, the correspondences of the critical points in signatures are made by bidirectional backward-merging dynamic time wrapping algorithm. Then, the subtle differences are calculated by classical dynamic time wrapping algorithm. These differences are utilized to train the HMM. The meanings of models states are defined as degrees of similarity, and the HMM topology is ergodic. The validity of the proposed approach is verified on SVC2004 signatures database.