Entropy based Biometric Template Clustering

Michele Nappi; Daniel Riccio; Maria De Marsico

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Paper

Entropy based Biometric Template Clustering

Topics: Clustering; Object Recognition

In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 560-563, 2013 , Barcelona, Spain

Authors: Michele Nappi ¹ ; Daniel Riccio ¹ and Maria De Marsico ²

Affiliations: ¹ University of Salerno, Italy ; ² Sapienza University of Rome, Italy

Keyword(s): Biometrics, Clustering, Entropy.

Related Ontology Subjects/Areas/Topics: Applications ; Clustering ; Object Recognition ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: Though speed and accuracy are two competing requirements for large scale biometric recognition, they both suffer from large database size. Clustering seems promising to reduce the search space. This can improve accuracy, but may even contrarily affect it by a poor selection of the candidate cluster for the search. We present a novel technique that exploits gallery entropy for clustering. The comparison with K-Means demonstrates that we achieve a better clustering result, yet without fixing the number of clusters a-priori.

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Paper citation in several formats:

Nappi, M.; Riccio, D. and De Marsico, M. (2013). Entropy based Biometric Template Clustering. In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-8565-41-9; ISSN 2184-4313, SciTePress, pages 560-563. DOI: 10.5220/0004266205600563

@conference{icpram13,
author={Michele Nappi. and Daniel Riccio. and Maria {De Marsico}.},
title={Entropy based Biometric Template Clustering},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2013},
pages={560-563},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004266205600563},
isbn={978-989-8565-41-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Entropy based Biometric Template Clustering
SN - 978-989-8565-41-9
IS - 2184-4313
AU - Nappi, M.
AU - Riccio, D.
AU - De Marsico, M.
PY - 2013
SP - 560
EP - 563
DO - 10.5220/0004266205600563
PB - SciTePress