{"title":"Semi-automatic BPT for Image Retrieval","authors":"Shirin Ghanbari, J. Woods, S. Lucas","doi":"10.1109/CBMI.2009.17","DOIUrl":null,"url":null,"abstract":"This paper presents a novel semi-automatic tool for content retrieval. A multi-dimension Binary Partition Tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multi-dimensional information can significantly enhance content retrieval results for natural images.","PeriodicalId":417012,"journal":{"name":"2009 Seventh International Workshop on Content-Based Multimedia Indexing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Seventh International Workshop on Content-Based Multimedia Indexing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMI.2009.17","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
This paper presents a novel semi-automatic tool for content retrieval. A multi-dimension Binary Partition Tree (BPT) is generated to perform object based image retrieval. The tree is colour based but has the advantage of incorporating spatial frequency to form semantically meaningful tree nodes. For retrieval, a node of the query image is matched against the nodes of the BPT of the database image. These are matched according to a combination of colour histograms, texture features and edge histograms. This semi-automatic tool allows users to have more freedom in their choice of query. The paper illustrates how the use of multi-dimensional information can significantly enhance content retrieval results for natural images.