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《Computer Engineering and Applications》 2009-03
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Image retrieval using contourlet transform

HUANG Chuan-bo,SHAO Jie,WAN Ming-hua,JIN ZhongDepartment of Computer Science,Nanjing University of Science and Technology,Nanjing 210094,China  
Based on the characteristics of good sparsity and capturing effectively the smooth contours in natural images for Con- tourlet transform.This paper completes texture analysis of the image on the demographic characteristics of Contourlet coefficient and pursues a filter algorithm.According to the statistical characteristics of Contourlet coefficients,Gauss model is used to demon- strate the statistics of those coefficients and extraction feature.The feature vector is weigh ted according to their degrees of the dispersion,and the feature with higher discrimination quality has bigger weight.At the same time,it obtains the final feature vec- tors by adding the statistic properties of the gray level co-occurrence matrix extracted from the sub band low-frequency.The tex- ture similarities of images are computed by the Euclidean’s distance with weight.Simulation results show that the method perform certain superiority in the retrieval results.
【Fund】: 国家自然科学基金(No.60473039);; 江苏省自然科学基金-青年科技创新人才启动项目资助(No.BK2007594)~~
【CateGory Index】: TP391.41
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7 Liu Li;Zhou Yajian;Zhang Bin;Yuan Kaiguo;Ding Haiyang;Guo Yucui;Information Security Center,Beijing University of Posts and Telecommunications;China Information Security Product Evaluation Authentication Center;Computer college,Beijing University of Posts and Telecommunications;Science College,Beijing University of Posts and Telecommunications;;Digital watermarking method for QR code images based on DCT and SVD[J];Infrared and Laser Engineering;2013-S2
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9 LOU Xiong-wei;HUANG De-cai;FANG Lu-ming;XU Ai-jun;College of Information Engineering,Zhejiang University of Technology;College of Information Engineering,Zhejiang A &F University;School of Computer Science & Technology College of Software,Zhejiang University of Technology;;Forest Fire Identification Method Based on Improved Genetic Algorithm and SVM[J];Computer Science;2014-08
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