On-Line Signature Verification With Two-Stage Statistical Models

Authors:
Liang Wan;Bin Wan
Affiliations:
Chinese University of Hong Kong;Huazhong University of Science and Technique
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

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Abstract

Signature verification is a challenging task, because only a small set of genuine samples can be acquired and usually no forgeries are available in real application. In this paper, we propose a new two-stage statistical system for automatic on-line signature verification. Our system is composed of a simplified GMM model for global signature features, and a discrete HMM model for local signature features. To be practical, we introduce specific simplification strategies for model building and training. Our system requires only 5 genuine samples for new users and relies on only 3 global parameters for quick and efficient system tuning. Experiments are conducted to verify the effectiveness of our system.