Bayesian MCMC for biometric person authentication incorporating on-line signature trajectories

Mitsuru Kondo, Daigo Muramatsu, Masahiro Sasaki, Takashi Matsumoto

研究成果: Conference contribution

抜粋

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 1825 genuine signatures and 4117 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.

元の言語English
ホスト出版物のタイトルProceedings of the IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
編集者M.H. Hamza
ページ269-273
ページ数5
出版物ステータスPublished - 2003 12 1
イベントProceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications - Rhodes, Greece
継続期間: 2003 6 302003 7 2

出版物シリーズ

名前Proceedings of the IASTED International Conference on Signal Processing, Pattern Reconition, and Applications

Conference

ConferenceProceedings of the IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Greece
Rhodes
期間03/6/3003/7/2

ASJC Scopus subject areas

  • Signal Processing
  • Development
  • Computer Vision and Pattern Recognition

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  • これを引用

    Kondo, M., Muramatsu, D., Sasaki, M., & Matsumoto, T. (2003). Bayesian MCMC for biometric person authentication incorporating on-line signature trajectories. : M. H. Hamza (版), Proceedings of the IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (pp. 269-273). (Proceedings of the IASTED International Conference on Signal Processing, Pattern Reconition, and Applications).