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Assessing Fingerprint Individuality Using EPIC

Summary: [This abstract is based on the authors' abstract.] This article presents a class of distributions of fingerprint features and a methodology for assessing fingerpring uniqueness using a Bayesian MCMC framework. Model flexibility is demonstrated with real ingerprint examples. A simulation procedure based on the previously described models determines Evidence of a Paired Impostor Correspondence (EPIC), which is used to measure fingerprint individuality.

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  • Topics: Statistics
  • Keywords: Distributions, Markov chains, Monte Carlo methods, Marked point processes, Mixture distribution
  • Author: Lim, Chae Young ; Dass, Sarat C.
  • Journal: Technometrics