Minqing Zhang, Xiaonan Chen, Xiaoyuan Yang, Juanli Sun
{"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}
引用次数: 1
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.