Hierarchical mixture models for assessing fingerprint individuality

DOI10.1214/09-AOAS266zbMath1185.62206arXiv1009.5778OpenAlexW2050726251MaRDI QIDQ965110

Sarat C. Dass, Mingfei Li

Publication date: 21 April 2010

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1009.5778

zbMATH Keywords

model-based clusteringGaussian mixturesBayesian inferencefingerprint individualityreversible jump Markov chain Monte Carlo methods

Mathematics Subject Classification ID

Bayesian inference (62F15) Image analysis in multivariate analysis (62H35) Applications of statistics (62P99) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (1)

A generalized mixed model framework for assessing fingerprint individuality in presence of varying image quality

Cites Work

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• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• Robust estimation of mixture complexity for count data
• On the similarity of identical twin fingerprints
• Practical Bayesian Density Estimation Using Mixtures of Normals
• Bayesian Model Selection in Finite Mixtures by Marginal Density Decompositions
• Bayesian Density Estimation and Inference Using Mixtures

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