{"title":"FIRM: fuzzily integrated region matching for content-based image retrieval","authors":"Yixin Chen, James Ze Wang, Jia Li","doi":"10.1145/500141.500237","DOIUrl":null,"url":null,"abstract":"We propose FIRM (Fuzzily Integrated Region Matching), an efficient and robust similarity measure for region-based image retrieval. Each image in our retrieval system is represented by a set of regions that are characterized by fuzzy sets. The FIRM measure, representing the overall similarity between two images, is defined as the similarity between two families of fuzzy sets. Compared with similarity measures based on individual regions and on all regions with crisp feature representations, our approach greatly reduces the influence of inaccurate segmentation. Experimental results based on a database of about 200,000 general-purpose images demonstrate improved accuracy, robustness, and high speed.","PeriodicalId":416848,"journal":{"name":"MULTIMEDIA '01","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '01","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/500141.500237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
We propose FIRM (Fuzzily Integrated Region Matching), an efficient and robust similarity measure for region-based image retrieval. Each image in our retrieval system is represented by a set of regions that are characterized by fuzzy sets. The FIRM measure, representing the overall similarity between two images, is defined as the similarity between two families of fuzzy sets. Compared with similarity measures based on individual regions and on all regions with crisp feature representations, our approach greatly reduces the influence of inaccurate segmentation. Experimental results based on a database of about 200,000 general-purpose images demonstrate improved accuracy, robustness, and high speed.
我们提出了FIRM (fuzzy Integrated Region Matching,模糊综合区域匹配),这是一种基于区域的图像检索的高效、鲁棒的相似度量。我们的检索系统中的每张图像都由一组由模糊集表征的区域表示。FIRM度量,表示两个图像之间的总体相似性,被定义为两个模糊集族之间的相似性。与基于单个区域和具有清晰特征表示的所有区域的相似度度量相比,我们的方法大大减少了不准确分割的影响。基于20万张通用图像数据库的实验结果表明,该方法具有较高的准确性、鲁棒性和速度。