Searching methods for biometric identification systems: Fundamental limits

F.M.J. Willems

doi:10.1109/ISIT.2009.5205870

Searching methods for biometric identification systems: Fundamental limits

F.M.J. Willems

Signal Processing Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

16 Citations (Scopus)

211 Downloads (Pure)

Abstract

We study two-stage search procedures for biometric identification systems in an information-theoretical setting. Our main conclusion is that clustering based on vector-quantization achieves the optimum trade-off between the number of clusters (cluster rate) and the number of individuals within a cluster (refinement rate). The notion of excess rate is introduced, a parameter which relates to the amount of clusters to which the individuals belong. We demonstrate that noisier observation channels lead to larger excess rates. © 2009 IEEE.

Original language	English
Title of host publication	2009 IEEE International Symposium on Information Theory, ISIT 2009, 28 June 2009 through 3 July 2009, Seoul
Pages	5205870-2245
DOIs	https://doi.org/10.1109/ISIT.2009.5205870
Publication status	Published - 2009

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title = "Searching methods for biometric identification systems: Fundamental limits",

abstract = "We study two-stage search procedures for biometric identification systems in an information-theoretical setting. Our main conclusion is that clustering based on vector-quantization achieves the optimum trade-off between the number of clusters (cluster rate) and the number of individuals within a cluster (refinement rate). The notion of excess rate is introduced, a parameter which relates to the amount of clusters to which the individuals belong. We demonstrate that noisier observation channels lead to larger excess rates. {\textcopyright} 2009 IEEE.",

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AB - We study two-stage search procedures for biometric identification systems in an information-theoretical setting. Our main conclusion is that clustering based on vector-quantization achieves the optimum trade-off between the number of clusters (cluster rate) and the number of individuals within a cluster (refinement rate). The notion of excess rate is introduced, a parameter which relates to the amount of clusters to which the individuals belong. We demonstrate that noisier observation channels lead to larger excess rates. © 2009 IEEE.

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DO - 10.1109/ISIT.2009.5205870

M3 - Conference contribution

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BT - 2009 IEEE International Symposium on Information Theory, ISIT 2009, 28 June 2009 through 3 July 2009, Seoul

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Searching methods for biometric identification systems: Fundamental limits

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