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Rotation-invariant Texture Image Retrieval Based on Multi-feature


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Rotation-invariant Texture Image Retrieval Based on Multi-feature
ZHU Zheng-li12ZHAO Chun-xia1HOU Ying-kun13FAN Yan4
1.School of Computer Science and Technology,NUST,Nanjing 210094,China; 2.College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,China; 3.School of Information Science and Technology,Taishan University,Taian 271021,China; 4.School of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang 212003,China
image retrieval rotational invariance nonsubsampled contourtlet transform gray level concurrence matrix similarity measurement
In order to eliminate the effect of image rotation on image retrieval,a novel rotation-invariant texture image retrieval algorithm is presented based on the nonsubsampled contourlet transform(NSCT),gray level concurrence matrix(GLCM)and novel similarity measurement.The NSCT has anisotropy and translation invariability.The GLCM reflects the direction,adjacency spacing relationship and range of variance change of the image.The rotation-invariant features are achieved by calculating the average energy and average standard deviation of all subbands at each NSCT scale,the mean and covariance of the second moment angle,inertia entropy,inertia moment,contrast points moment of the GLCM.A novel similarity measure is presented to improve the retrieval performance of texture images.Experimental results demonstrate that:compared with the dual tree-complex wavelet transform based approach,the image retrieval algorithm improves the retrieval accuracy from 73.28% to 80.71% for the rotated database of 640 images.


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Last Update: 2012-10-12