Texture Classification Using Hierarchical Linear Discriminant Space

Yousun KANG  Ken'ichi MOROOKA  Hiroshi NAGAHASHI  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E88-D   No.10   pp.2380-2388
Publication Date: 2005/10/01
Online ISSN: 
DOI: 10.1093/ietisy/e88-d.10.2380
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
Keyword: 
texture classification,  hierarchical discriminant analysis,  

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Summary: 
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.