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Joint Statistics and Biostatistics & Medical Informatics Seminar


A Statistical Model for Signatures

Ian W. McKeague, Ph.D., Department of Statistics, Florida State University

Friday, April 23, 2003, 4-5 pm

1221 Computer Sciences and Statistics Center (CSSC), 1210 W. Dayton St.

ABSTRACT

A Bayesian model for off-line signature analysis involving the representation of a signature through its curvature is developed. The prior model makes use of a spatial point process for specifying the knots in an approximation restricted to a buffer region close to a template curvature, along with an independent time warping mechanism. In this way, prior shape information about the signature can be built into the analysis. The observation model is based on additive white noise superimposed on the underlying curvature. The approach is implemented using MCMC and applied to a collection of documented instances of Shakespeare's signature.


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