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International Conference on Intelligent Computing

ICIC 2008: Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues pp 92–97Cite as

A New Unsupervised Approach to Face Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5226))

Abstract

A new unsupervised approach to face recognition is proposed in this paper. Shape and color entropy is presented to descript face features. Firstly, images are pre-processed including face normalization and image segmentation and so on. Secondly, by using the information entropy theory, the method defines the color and shape entropy of the face images, respectively. Finally, an integrated similarity measurement framework is presented by computing mutual information between images according to these entropies. Compared with other methods of feature description, experiments indicate that this approach is more effective and efficient.

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Author information

Authors and Affiliations

  1. School of Natural Science, East China Jiaotong University, Nanchang, 330013, China

    Zizhu Fan & Ergen Liu

Authors
  1. Zizhu Fan
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  2. Ergen Liu
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Editor information

Editors and Affiliations

  1. Department of Automation, University of Science and Technology of China, 230026, Hefei, Anhui, China

    De-Shuang Huang

  2. Applied Computational Intelligence Laboratory, P.O. Box

    Donald C. Wunsch II

  3. Arlington, USA

    Daniel S. Levine

  4. Graduate School of Electrical Engineering, University of Ulsan, Korea, San 29, Mugeo-Dong, 680 - 749, Nam-Ku, Ulsan, Korea

    Kang-Hyun Jo

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© 2008 Springer-Verlag Berlin Heidelberg

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Fan, Z., Liu, E. (2008). A New Unsupervised Approach to Face Recognition. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_13

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  • DOI: https://doi.org/10.1007/978-3-540-87442-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87440-9

  • Online ISBN: 978-3-540-87442-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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