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《Journal of Yunnan University of Nationalities(Natural Sciences Edition)》 2011-06
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Image Classification by Using Contourlet Transform and SVM

XIA Wei,ZHAO Yong,ZHOU Wei-hong(School of Mathematics and Computer Science,Yunnan University of Nationalities,Kunming 650031,China)  
Because Contourlet transform has the features of multi-resolution,time-frequency localization,directionality and anisotropy,it can well capture an image's profile features well,while using the Contourlet coefficients can help the feature detection.This paper proposes an image classification method based on Contourlet transform and SVM.First,Contourlet transform is used to deal with color images after grayscale,then the low frequency coefficients are classified as the semantic features of images,and last,SVM classifier is used to classify images.The experimental results show that this method has better classification results.
【Fund】: 云南省教育厅科学研究基金(2011J049;09Y0258)
【CateGory Index】: TP391.41
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