Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification

被引:82
|
作者
Sengur, Abdulkadir [1 ]
机构
[1] Firat Univ, Dept Elect & Comp Sci, TR-23119 Elazig, Turkey
关键词
wavelet decomposition; ANFIS; texture classification; feature extraction; entropy; energy correlation;
D O I
10.1016/j.eswa.2007.02.032
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The wavelet domain features have been intensively used for texture classification and texture segmentation with encouraging results. More of the proposed multi resolution texture analysis methods are quite successful, but all the applications of the texture analysis so far are limited to gray scale images. This paper investigates the usage of Wavelet transform (WT) and Adaptive neuro-fuzzy inference system (ANFIS) for color texture classification problem. The proposed scheme composed of a wavelet domain feature extractor and an ANFIS classifier. Both entropy and energy features are used on wavelet domain. Different color spaces are considered in the experimental studies. The performed experimental studies show the effectiveness of the wavelet transform and ANFIS structure for color texture classification problem. The overall success rate is over 96%. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2120 / 2128
页数:9
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