@inbook{8189abebb11a497383eb28b13d96ad3e,
title = "A Bayesian MCMC On-line Signature Verification",
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 peninclination 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 skilled1 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.",
author = "Mitsuru Kondo and Daigo Muramatsu and Masahiro Sasaki and Takashi Matsumoto",
year = "2003",
doi = "10.1007/3-540-44887-x_64",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "540--548",
editor = "Josef Kittler and Nixon, {Mark S.}",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}