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《Opto-Electronic Engineering》 2009-04
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Texture Analysis Based on Coefficient Relationship Co-occurrence Matrix and SVM

LIU Qing1,2,LIN Tu-sheng1,WANG Xiao-jun2(1.School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,China;2.School of Technology,Jinggangshan University,Ji'an 343009,Jiangxi Province,China)  
Texture is an important image feature.A novel texture feature extraction technique is proposed based on coefficient co-occurrence matrix of discrete wavelet frame transformed image,which captures the information about relationship between each high frequency subband and low frequency subband of the decomposed image at the corresponding level.It is not independent to extract the information of each subband coefficient.Considering that the Support Vector Machine(SVM) has advantages of resolving the small-sample statistics and generalizing ability,the classification performance is analyzed by using the SVM classifier.The experimental results demonstrate the effectiveness of our proposed texture feature in achieving the improved classification performance.
【Fund】: 国家自然科学基金资助项目(60472006);; 广东省自然科学基金团队研究项目(04205783);; 江西省教育厅2008年度科技计划资助项目(GJJ08414)
【CateGory Index】: TP391.41
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