A Bayesian MCMC on-line signature verification

  • Authors:

  • Mitsuru Kondo;Daigo Muramatsu;Masahiro Sasaki;Takashi Matsumoto

  • Affiliations:

  • Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University, Tokyo, Japan;Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University, Tokyo, Japan;Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University, Tokyo, Japan;Department of Electrical, Electronics and Computer Engineering, Graduate School of Science and Engineering, Waseda University, Tokyo, Japan

  • Venue:
  • AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
  • Year:
  • 2003

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Abstract

Authentication of individuals is rapidly becoming an important issue. The authors have previously proposed a pen-input online signature verification algorithm. The algorithm considers writer's signature as a trajectory of pen-position, pen-pressure and pen-inclination which evolves over time, so that it is dynamic and biometric. In our previous work, genuine signatures were separated from forgery signatures in a linear manner. This paper proposes a new algorithm which performs nonlinear separation using Bayesian MCMC (Markov Chain Monte Carlo). A preliminary experiment is performed on a database consisting of 1852 genuine signatures and 3170 skilled forgery signatures from fourteen individuals. FRR 0.81% and FAR 0.87% are achieved. Since no fine tuning was done, this preliminary result looks very promising.