A statistical model for signature verification

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

10 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)231-241
Journal / PublicationJournal of the American Statistical Association
Volume100
Issue number469
Publication statusPublished - Mar 2005
Externally publishedYes

Abstract

A Bayesian model for off-line signature verification 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 Markov chain Monte Carlo and applied to a collection of documented instances of William Shakespeare's signature. © 2005 American Statistical Association.

Research Area(s)

  • Bayesian nonparametric regression, Biometric identification, Functional data analysis, Shape theory, Spatial point processes, Time warping

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