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Human Face Recognition Using Modified Hausdorff ARTMAP

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Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3645))

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Abstract

This paper proposes a new neural network approach specifically designed for solving two dimensional binary image recognition problems. The proposed neural network is an extension of the Hausdorff ARTMAP introduced by Thammano and Rungruang [1]. The objectives of this research are to improve the accuracy and correct the drawbacks of the original network. The performance of this proposed model has been compared with that of the original Hausdorff ARTMAP. The experimental results on two benchmark databases, the ORL and Yale face databases, show that the proposed network surpasses the original Hausdorff ARTMAP in both performance and processing time.

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Author information

Authors and Affiliations

  1. King Mongkut’s Institute of Technology Ladkrabang, Faculty of Information Technology, Bangkok, 10520, Thailand

    Arit Thammano & Songpol Ruensuk

Authors
  1. Arit Thammano
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  2. Songpol Ruensuk
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Editor information

Editors and Affiliations

  1. Intelligent Computing Lab, Institute of Intelligent Machines, Chinese Academy of Sciences, China

    De-Shuang Huang

  2. School of Computer & Information Technology, Beijing Jiaotong University, 100044, Beijing, P.R. China

    Xiao-Ping Zhang

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

    Guang-Bin Huang

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© 2005 Springer-Verlag Berlin Heidelberg

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Thammano, A., Ruensuk, S. (2005). Human Face Recognition Using Modified Hausdorff ARTMAP. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538356_26

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  • DOI: https://doi.org/10.1007/11538356_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28227-3

  • Online ISBN: 978-3-540-31907-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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