{"title":"基于内容的双树复小波变换图像检索","authors":"Stella Vetova, Ivan Ivanov","doi":"10.1109/MCSI.2014.51","DOIUrl":null,"url":null,"abstract":"The following paper presents a novel and effective algorithm for Content-Based Image Retrieval. To design it we used the Dual-Tree Complex Wavelet Transform for image feature extraction and Hausdorff distance to compute similarity distance between the feature vector of the query-image and all the image feature vectors stored in the image database. Then, we performed experiments to estimate the effectiveness of the proposed algorithm which showed high values of precision.","PeriodicalId":202841,"journal":{"name":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","volume":"235 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Content -- Based Image Retrieval Using the Dual-Tree Complex Wavelet Transform\",\"authors\":\"Stella Vetova, Ivan Ivanov\",\"doi\":\"10.1109/MCSI.2014.51\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The following paper presents a novel and effective algorithm for Content-Based Image Retrieval. To design it we used the Dual-Tree Complex Wavelet Transform for image feature extraction and Hausdorff distance to compute similarity distance between the feature vector of the query-image and all the image feature vectors stored in the image database. Then, we performed experiments to estimate the effectiveness of the proposed algorithm which showed high values of precision.\",\"PeriodicalId\":202841,\"journal\":{\"name\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"volume\":\"235 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Mathematics and Computers in Sciences and in Industry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSI.2014.51\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Mathematics and Computers in Sciences and in Industry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSI.2014.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Content -- Based Image Retrieval Using the Dual-Tree Complex Wavelet Transform
The following paper presents a novel and effective algorithm for Content-Based Image Retrieval. To design it we used the Dual-Tree Complex Wavelet Transform for image feature extraction and Hausdorff distance to compute similarity distance between the feature vector of the query-image and all the image feature vectors stored in the image database. Then, we performed experiments to estimate the effectiveness of the proposed algorithm which showed high values of precision.
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