Texture Classification Using Hierarchical Linear Discriminant Space

Yousun KANG; Ken'ichi MOROOKA; Hiroshi NAGAHASHI

doi:10.1093/ietisy/e88-d.10.2380

Texture Classification Using Hierarchical Linear Discriminant Space

Yousun KANG, Ken'ichi MOROOKA, Hiroshi NAGAHASHI

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E88-D No.10 pp.2380-2388

Publication Date: 2005/10/01

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DOI: 10.1093/ietisy/e88-d.10.2380

Type of Manuscript: PAPER

Category: Image Recognition, Computer Vision

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Yousun KANG, Ken'ichi MOROOKA, Hiroshi NAGAHASHI, "Texture Classification Using Hierarchical Linear Discriminant Space" in IEICE TRANSACTIONS on Information, vol. E88-D, no. 10, pp. 2380-2388, October 2005, doi: 10.1093/ietisy/e88-d.10.2380.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.10.2380/_p

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@ARTICLE{e88-d_10_2380,
author={Yousun KANG, Ken'ichi MOROOKA, Hiroshi NAGAHASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Texture Classification Using Hierarchical Linear Discriminant Space},
year={2005},
volume={E88-D},
number={10},
pages={2380-2388},
abstract={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.},
keywords={},
doi={10.1093/ietisy/e88-d.10.2380},
ISSN={},
month={October},}

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TY - JOUR
TI - Texture Classification Using Hierarchical Linear Discriminant Space
T2 - IEICE TRANSACTIONS on Information
SP - 2380
EP - 2388
AU - Yousun KANG
AU - Ken'ichi MOROOKA
AU - Hiroshi NAGAHASHI
PY - 2005
DO - 10.1093/ietisy/e88-d.10.2380
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2005
AB - 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.
ER -