{"title":"基于内容的图像检索中颜色的“形状”","authors":"Renato O. Stehling, M. Nascimento, A. Falcão","doi":"10.1145/357744.361911","DOIUrl":null,"url":null,"abstract":"Color is a commonly used feature for realizing content-based image retrieval (CBIR). Towards this goal, this paper presents a new approach for CBIR which is based on well known and widely used color histograms. Contrasting to previous approaches, such as using a single color histogram for the whole image, or local color histograms for a fixed number of image cells, the one we propose (named Color Shape) uses a variable number of histograms, depending only on the actual number of colors present in the image. Our experiments using a large set of heterogeneous images and pre-defined query/answer sets show that the Color Shape approach offers good retrieval quality with relatively low space overhead, outperforming previous approaches.","PeriodicalId":234597,"journal":{"name":"MULTIMEDIA '00","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":"{\"title\":\"On “shapes” of colors for content-based image retrieval\",\"authors\":\"Renato O. Stehling, M. Nascimento, A. Falcão\",\"doi\":\"10.1145/357744.361911\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Color is a commonly used feature for realizing content-based image retrieval (CBIR). Towards this goal, this paper presents a new approach for CBIR which is based on well known and widely used color histograms. Contrasting to previous approaches, such as using a single color histogram for the whole image, or local color histograms for a fixed number of image cells, the one we propose (named Color Shape) uses a variable number of histograms, depending only on the actual number of colors present in the image. Our experiments using a large set of heterogeneous images and pre-defined query/answer sets show that the Color Shape approach offers good retrieval quality with relatively low space overhead, outperforming previous approaches.\",\"PeriodicalId\":234597,\"journal\":{\"name\":\"MULTIMEDIA '00\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MULTIMEDIA '00\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/357744.361911\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MULTIMEDIA '00","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/357744.361911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On “shapes” of colors for content-based image retrieval
Color is a commonly used feature for realizing content-based image retrieval (CBIR). Towards this goal, this paper presents a new approach for CBIR which is based on well known and widely used color histograms. Contrasting to previous approaches, such as using a single color histogram for the whole image, or local color histograms for a fixed number of image cells, the one we propose (named Color Shape) uses a variable number of histograms, depending only on the actual number of colors present in the image. Our experiments using a large set of heterogeneous images and pre-defined query/answer sets show that the Color Shape approach offers good retrieval quality with relatively low space overhead, outperforming previous approaches.