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Novel Metrics for Face Recognition Using Local Binary Patterns

  • Conference paper
Knowledge-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6881))

Abstract

The paper presents a novel approach to face recognition using Local Binary Patterns (LBP) with the novel soft chi square and soft power metrics. Results of intensive experiments on two public databases, FERET and AT&T, show that these new metrics are efficient and flexible for real-time face recognition applications. They can reduce time performance and also achieve high recognition rate.

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Author information

Authors and Affiliations

  1. Faculty of Information Sciences and Engineering, University of Canberra, ACT, 2601, Australia

    Len Bui, Dat Tran, Xu Huang & Girija Chetty

Authors
  1. Len Bui
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  2. Dat Tran
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  3. Xu Huang
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  4. Girija Chetty
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Editor information

Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of omputer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Sakai, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Mawson Lakes, 5095, Adelaide, SA, Australia

    Lakhmi C. Jain

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© 2011 Springer-Verlag Berlin Heidelberg

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Bui, L., Tran, D., Huang, X., Chetty, G. (2011). Novel Metrics for Face Recognition Using Local Binary Patterns. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23851-2_45

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  • DOI: https://doi.org/10.1007/978-3-642-23851-2_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23850-5

  • Online ISBN: 978-3-642-23851-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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