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

作者:

Highlights:

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%.

论文关键词:Wavelet decomposition,ANFIS,Texture classification,Feature extraction,Entropy,Energy correlation

论文评审过程:Available online 4 March 2007.

论文官网地址:https://doi.org/10.1016/j.eswa.2007.02.032