Texture Classification Using Hierarchical Linear Discriminant Space

  • KANG Yousun
    Imaging Science and Engineering Laboratory, Tokyo Institute of Technology
  • MOROOKA Ken'ichi
    Imaging Science and Engineering Laboratory, Tokyo Institute of Technology
  • NAGAHASHI Hiroshi
    Imaging Science and Engineering Laboratory, Tokyo Institute of Technology

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抄録

As a representative of the linear discriminant analysis, the Fisher method is most widely used in practice and it is very effective in two-class classification. However, when it is expanded to a multi-class classification problem, the precision of its discrimination may become worse. A main reason is an occurrence of overlapped distributions on the discriminant space built by Fisher criterion. In order to take such overlaps among classes into consideration, our approach builds a new discriminant space by hierarchically classifying the overlapped classes. In this paper, we propose a new hierarchical discriminant analysis for texture classification. We divide the discriminant space into subspaces by recursively grouping the overlapped classes. In the experiment, texture images from many classes are classified based on the proposed method. We show the outstanding result compared with the conventional Fisher method.

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詳細情報 詳細情報について

  • CRID
    1570854177488822784
  • NII論文ID
    110003214167
  • NII書誌ID
    AA10826272
  • ISSN
    09168532
  • 本文言語コード
    en
  • データソース種別
    • CiNii Articles

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