关键词: Contourlet变换, 广义高斯分布, 支持向量机, 相关反馈, 纹理图像检索

Abstract: A new texture image retrieval method based on Contourlet transform and support vector machines （SVMs） is proposed. In this method， the energies and the generalized Gaussian distribution （GGD） parameters are used to represent the Contourlet subband features. Using the representations， a two-run SVM retrieval algorithm which employs an one-class SVM followed by a two-class SVM is proposed to carry out the perceptual similarity measurement. Compared with existing texture image retrieval methods， the proposed retrieval scheme is demonstrated respectively to be effective on the VisTex database of 640 texture images and the Brodatz database of 1 760 texture images. Experimental results have shown that the proposed retrieval scheme can attain 99.38% and 98.07% of the average rates respectively for the two databases.

Key words: Contourlet transform, generalized Gaussian distribution, support vector machine, relevance feedback, texture image retrieval