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Face recognition using kernel entropy component analysis
Neurocomputing 74 (2011) 1053–1057Contents lists available at ScienceDirectNeurocomputing0925-23
doi:10.1
n Corr
E-m
sharmil
natalia.djournal homepage: /locate/neucomLettersFace recognition using kernel entropy component analysisB.H. Shekar a, M. Sharmila Kumari b,n, Leonid M. Mestetskiy c, Natalia F. Dyshkant c
a Department of Computer Science, Mangalore University, Mangalore, Karnataka, India
b Department of Computer Science Engineering, PA College of Engineering, Mangalore, Karnataka, India
c Department of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russiaa r t i c l e i n f o
Article history:
Received 7 June 2010
Accepted 17 October 2010Communicated by L.C. Jain
the best principal component vectors that are subsequently used for pattern projection to a lower-
dimensional space. Extensive experimentation on Yale and UMIST face database has been conducted to
Available online 17 December 2010
Keywords:
Principal component analysis
Entropy component analysis
Eigenface
Face recognition12/$ - see front matter 2010 Elsevier B.V. A
016/j.neucom.2010.10.012
esponding author.
ail addresses: bhshekar@ (B.H. Shek
abp@ (M. Sharmila Kumari), mestlm
yshkant@ (N.F. Dyshkant).a b s t r a c t
In this letter, we have reported a new face recognition algorithm based on Renyi entropy component
analysis. In the proposedmodel, kernel-basedmethodology is integratedwith entropy analysis to choose
reveal the performance of the entropy based principal component analysis method and comparative
analysis is made with the kernel principal component analysis method to signify the importance of
selection of principal component vectors based on entropy information rather based only onmagnitude of
eigenvalues.
2010 Elsevier B.V. All rights reserved.1. Introduction
In the current decade and the last decade,wehavewitnessed the
tremendous growth of research in the field of biometrics, in
particular on face recognition because of its wide acceptability in
several app
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