Minqing Zhang, Xiaonan Chen, Xiaoyuan Yang, Juanli Sun
{"title":"一种基于轮廓的图像检索方法","authors":"Minqing Zhang, Xiaonan Chen, Xiaoyuan Yang, Juanli Sun","doi":"10.1109/CISE.2010.5677223","DOIUrl":null,"url":null,"abstract":"Compared to color and texture, contour is closer to human vision. So contour-based image retrieval has been a hot topic. However, existing methods can't obtain object contour effectively, which makes contour description and matching more difficult. To address these problems, this paper uses KPAC (Kernel-based Parametric Active Contour) to obtain the object contour, and proposes a novel method called LICS (Local Important Contour Sequence) for feature description and matching. Experimental results demonstrate that this approach achieves state-of-the-art performance in image retrieval.","PeriodicalId":232832,"journal":{"name":"2010 International Conference on Computational Intelligence and Software Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Contour-Based Method on Image Retrieval\",\"authors\":\"Minqing Zhang, Xiaonan Chen, Xiaoyuan Yang, Juanli Sun\",\"doi\":\"10.1109/CISE.2010.5677223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Compared to color and texture, contour is closer to human vision. So contour-based image retrieval has been a hot topic. However, existing methods can't obtain object contour effectively, which makes contour description and matching more difficult. To address these problems, this paper uses KPAC (Kernel-based Parametric Active Contour) to obtain the object contour, and proposes a novel method called LICS (Local Important Contour Sequence) for feature description and matching. Experimental results demonstrate that this approach achieves state-of-the-art performance in image retrieval.\",\"PeriodicalId\":232832,\"journal\":{\"name\":\"2010 International Conference on Computational Intelligence and Software Engineering\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Computational Intelligence and Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISE.2010.5677223\",\"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 Computational Intelligence and Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISE.2010.5677223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compared to color and texture, contour is closer to human vision. So contour-based image retrieval has been a hot topic. However, existing methods can't obtain object contour effectively, which makes contour description and matching more difficult. To address these problems, this paper uses KPAC (Kernel-based Parametric Active Contour) to obtain the object contour, and proposes a novel method called LICS (Local Important Contour Sequence) for feature description and matching. Experimental results demonstrate that this approach achieves state-of-the-art performance in image retrieval.