On texture classification using fractal dimension

被引：20

作者：

Chen, YQ ^{[1
]}

Bi, G ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

来源：

INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE | 1999年 / 13卷 / 06期

关键词：

texture analysis; image processing; pattern recognition; fractal dimension;

D O I：

10.1142/S0218001499000513

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The fractal dimension has been studied as a feature for texture analysis. It has been found that the fractal dimension is not an effective image texture measure but little is known about the reasons for the fractal dimension failing to be effective for texture analysis. This paper investigates into the underlying causes why the fractal dimension is not an effective image texture feature. Four mathematical properties have been identified which are responsible for the fractal dimension's ineffectiveness. The experimental results show that while the fractal dimension itself is hardly an effective feature for texture classification, it can considerably enhance other feature sets.

引用

页码：929 / 943

页数：15

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