{"title":"基于内容的分层树匹配子图像检索","authors":"Jie Luo, M. Nascimento","doi":"10.1145/951676.951689","DOIUrl":null,"url":null,"abstract":"This paper deals with the problem of finding images that contain a given query image, the so-called content-based sub-image retrieval. We propose an approach based on a hierarchical tree that encodes the color feature of image tiles which are in turn stored as an index sequence. The index sequences of both candidate images and the query sub-image are then compared in order to rank the database images suitability with respect to the query. In our experiments, using 10,000 images and disk-resident metadata, for 60Σ (80Σ) of the queries the relevant image, i.e., the one where the query sub-image was extracted from, was found among the first 10 (50) retrieved images in about 0.15 sec.","PeriodicalId":415406,"journal":{"name":"ACM International Workshop on Multimedia Databases","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Content based sub-image retrieval via hierarchical tree matching\",\"authors\":\"Jie Luo, M. Nascimento\",\"doi\":\"10.1145/951676.951689\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the problem of finding images that contain a given query image, the so-called content-based sub-image retrieval. We propose an approach based on a hierarchical tree that encodes the color feature of image tiles which are in turn stored as an index sequence. The index sequences of both candidate images and the query sub-image are then compared in order to rank the database images suitability with respect to the query. In our experiments, using 10,000 images and disk-resident metadata, for 60Σ (80Σ) of the queries the relevant image, i.e., the one where the query sub-image was extracted from, was found among the first 10 (50) retrieved images in about 0.15 sec.\",\"PeriodicalId\":415406,\"journal\":{\"name\":\"ACM International Workshop on Multimedia Databases\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM International Workshop on Multimedia Databases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/951676.951689\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM International Workshop on Multimedia Databases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/951676.951689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Content based sub-image retrieval via hierarchical tree matching
This paper deals with the problem of finding images that contain a given query image, the so-called content-based sub-image retrieval. We propose an approach based on a hierarchical tree that encodes the color feature of image tiles which are in turn stored as an index sequence. The index sequences of both candidate images and the query sub-image are then compared in order to rank the database images suitability with respect to the query. In our experiments, using 10,000 images and disk-resident metadata, for 60Σ (80Σ) of the queries the relevant image, i.e., the one where the query sub-image was extracted from, was found among the first 10 (50) retrieved images in about 0.15 sec.