{"title":"Contourlet-1.3纹理图像检索系统","authors":"Xinwu Chen, Guang-Li Yu, Junbin Gong","doi":"10.1109/ICWAPR.2010.5576449","DOIUrl":null,"url":null,"abstract":"Contourlet transform has better performance in directional information representation than wavelet transform and has been studied by many researchers in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, an anti-aliasing contourlet-1.3 transform based texture image retrieval system was proposed in this paper. In the system, the contourlet transform was constructed by anti-aliasing critical subsampled Laplacian pyramid cascaded by critical subsampled directional filter banks, sub-bands energy and standard deviations in contourlet domain are cascaded to form feature vectors, and the similarity metric is Canberra distance. Experimental results show that contourlet-1.3 transform based image retrieval system is superior to those of the original contourlet transform, nun-subsampled contourlet system and contourlet-2.3 under the same system structure with almost same length of feature vectors, retrieval time and memory needed; and anti-aliasing contourlet decomposition structure parameter can make significant effects on retrieval rates, especially scale number.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Contourlet-1.3 texture image retrieval system\",\"authors\":\"Xinwu Chen, Guang-Li Yu, Junbin Gong\",\"doi\":\"10.1109/ICWAPR.2010.5576449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Contourlet transform has better performance in directional information representation than wavelet transform and has been studied by many researchers in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, an anti-aliasing contourlet-1.3 transform based texture image retrieval system was proposed in this paper. In the system, the contourlet transform was constructed by anti-aliasing critical subsampled Laplacian pyramid cascaded by critical subsampled directional filter banks, sub-bands energy and standard deviations in contourlet domain are cascaded to form feature vectors, and the similarity metric is Canberra distance. Experimental results show that contourlet-1.3 transform based image retrieval system is superior to those of the original contourlet transform, nun-subsampled contourlet system and contourlet-2.3 under the same system structure with almost same length of feature vectors, retrieval time and memory needed; and anti-aliasing contourlet decomposition structure parameter can make significant effects on retrieval rates, especially scale number.\",\"PeriodicalId\":219884,\"journal\":{\"name\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Wavelet Analysis and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWAPR.2010.5576449\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Wavelet Analysis and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWAPR.2010.5576449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Contourlet transform has better performance in directional information representation than wavelet transform and has been studied by many researchers in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, an anti-aliasing contourlet-1.3 transform based texture image retrieval system was proposed in this paper. In the system, the contourlet transform was constructed by anti-aliasing critical subsampled Laplacian pyramid cascaded by critical subsampled directional filter banks, sub-bands energy and standard deviations in contourlet domain are cascaded to form feature vectors, and the similarity metric is Canberra distance. Experimental results show that contourlet-1.3 transform based image retrieval system is superior to those of the original contourlet transform, nun-subsampled contourlet system and contourlet-2.3 under the same system structure with almost same length of feature vectors, retrieval time and memory needed; and anti-aliasing contourlet decomposition structure parameter can make significant effects on retrieval rates, especially scale number.