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Image Recognition with a Large Database Using Method of Directed Enumeration Alternatives Modification

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6743))

Abstract

A new modification of the method of directed alternatives’ enumeration using the Kullback–Leibler discrimination information is proposed for half-tone image recognition.Results of an experimental study in the problem of face images recognition with a large database are presented. It is shown that the proposed modification is characterized by increased speed of image recognition (5-10 times vs exhaustive search).

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Author information

Authors and Affiliations

  1. National Research University – Higher School of Economics, N. Novgorod, Russia

    Andrey V. Savchenko

Authors
  1. Andrey V. Savchenko
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Editor information

Editors and Affiliations

  1. State University Higher School of Economics, Pokrovskiy Bd. 11, 109028, Moscow, Russia

    Sergei O. Kuznetsov

  2. Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  3. Department of Computer Science, University of Regina, 3737 Wascana Parkway, S4S 0A2, Regina, SK, Canada

    Daryl H. Hepting

  4. Birbeck University of London, Malet Street, WC1E 7HX, London, UK

    Boris G. Mirkin

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© 2011 Springer-Verlag Berlin Heidelberg

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Savchenko, A.V. (2011). Image Recognition with a Large Database Using Method of Directed Enumeration Alternatives Modification. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2011. Lecture Notes in Computer Science(), vol 6743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21881-1_52

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  • DOI: https://doi.org/10.1007/978-3-642-21881-1_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21880-4

  • Online ISBN: 978-3-642-21881-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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