Texture Image Classification Using Non-subsampled Contourlet Transform and Support Vector Machines

被引：0

作者：

Li, Yi ^{[1
]}

Liu, Guanzhong ^{[2
]}

机构：

[1] Cent S Univ, Sch Business, Changsha, Hunan, Peoples R China

[2] Tsinghua Univ, Acad Arts & Design, Beijing, Peoples R China

来源：

SECOND INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 1, PROCEEDINGS | 2009年

关键词：

texture classification; non-subsampled contourlet transform; support vector machines; wavelet transform;

D O I：

10.1109/ISCID.2009.88

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a new approach to characterize texture image at multiresolution using the non-subsampled contourlet transform, a new geometrical multiresolution transform. The support vector machines (SVMs), which have demonstrated excellent performance in a variety of pattern recognition problems, are used as classifiers. The Classification experiments with 20 Brodatz textures indicate that the NSCT and SVM approach is superior to standard wavelet transform method.

引用

页码：322 / 324

页数：3

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