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

Sarat C. Dass; Chae Young Lim; Tapabrata Maiti

doi:10.1214/14-AOAS734

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

Sarat C. Dass, Chae Young Lim, Tapabrata Maiti

School of Mathematical & Computer Sciences

Research output: Contribution to journal › Article

1 Citation (Scopus)

Original language	English
Pages (from-to)	1314-1340
Journal	Annals of Applied Statistics
Volume	8
Issue number	3
DOIs	https://doi.org/10.1214/14-AOAS734
Publication status	Published - Sep 2014

Keywords

Biometric authentication
fingerprint-based authentication
individuality
GLMMs
Bayesian inference
Laplace approximation

Access to Document

10.1214/14-AOAS734

Cite this

Dass, S. C., Lim, C. Y., & Maiti, T. (2014). A generalized mixed model framework for assessing fingerprint individuality in presence of varying image quality. Annals of Applied Statistics, 8(3), 1314-1340. https://doi.org/10.1214/14-AOAS734

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title = "A generalized mixed model framework for assessing fingerprint individuality in presence of varying image quality",

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author = "Dass, {Sarat C.} and Lim, {Chae Young} and Tapabrata Maiti",

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AU - Dass, Sarat C.

AU - Lim, Chae Young

AU - Maiti, Tapabrata

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KW - fingerprint-based authentication

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KW - GLMMs

KW - Bayesian inference

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DO - 10.1214/14-AOAS734

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