New methods for analysing colour texture based on the Karhunen-Loeve transform and quantification

被引:11
作者
Foucherot, I [1 ]
Gouton, P [1 ]
Devaux, JC [1 ]
Truchetet, F [1 ]
机构
[1] Univ Bourgogne, UMR 5158 CNRS, Lab Elect Informat Image, F-21078 Dijon, France
关键词
colour texture; Karhunen-Loeve transform; local linear transform; co-occurrence matrix; run lengths;
D O I
10.1016/j.patcog.2004.02.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this article, we offer an original study on the analysis of the texture of colour images based on Local Linear Transforms (LLT). Our colour approach is based on the separability of the data which reduces the number of texture parameters. We also propose the extension of Run Lengths (RL) and Co-occurrence Matrixes (CM) to colour images. In this respect, two different ways were explored (data merging and quantification). We finally present a comparative study showing the efficiency of the first method (LLT) as well as the complementary nature of the other methods (RL, CM). (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1661 / 1674
页数:14
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