{"title":"Image indexing and similarity retrieval based on a new spatial relation model","authors":"Ying-Hong Wang","doi":"10.1109/CDCS.2001.918736","DOIUrl":null,"url":null,"abstract":"The spatial relation model is an important technique for image indexing and retrieval in image or multimedia databases. 2D strings and its variants are proposed to support the representation of spatial relationships. A novel spatial knowledge representation model named \"Two Dimension Begin-End boundary string\" (2D B/spl epsi/-string) is proposed. The 2D B/spl epsi/-string represents an icon by its MBR boundaries. By applying a number of \"dummy objects\", the 2D B/spl epsi/-string can intuitively and naturally represent the pictorial spatial information without any spatial operator. In addition, an image similarity evaluation method based on the modified \"Longest Common Subsequence\" (LCS) algorithm is presented. By using the proposed evaluation method, not only can those images for which all the icons and their spatial relationships fully agree with the query image be sifted out, but also those images whose partial icons and/or spatial relationships are similar to the query image. It resolves the problems of query targets and/or spatial relationships not being certain. Our representation model and similarity evaluation also simplify the retrieval progress of linear transformations, including image rotation and reflection.","PeriodicalId":273489,"journal":{"name":"Proceedings 21st International Conference on Distributed Computing Systems Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 21st International Conference on Distributed Computing Systems Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDCS.2001.918736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

空间关系模型是图像或多媒体数据库中图像索引和检索的一项重要技术。提出了二维字符串及其变体来支持空间关系的表示。提出了一种新的空间知识表示模型“二维始末边界字符串”(2D B/spl epsi/-string)。2D B/spl epsi/-字符串通过其MBR边界表示图标。通过应用若干“虚拟对象”,二维B/spl epsi/-string可以直观、自然地表示图像空间信息,无需任何空间算子。此外,提出了一种基于改进的“最长公共子序列”(LCS)算法的图像相似性评价方法。利用所提出的评价方法,不仅可以筛选出所有图标及其空间关系与查询图像完全一致的图像,而且可以筛选出部分图标和/或空间关系与查询图像相似的图像。它解决了查询目标和/或空间关系不确定的问题。我们的表示模型和相似度评价也简化了线性变换的检索过程,包括图像旋转和反射。
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Image indexing and similarity retrieval based on a new spatial relation model
The spatial relation model is an important technique for image indexing and retrieval in image or multimedia databases. 2D strings and its variants are proposed to support the representation of spatial relationships. A novel spatial knowledge representation model named "Two Dimension Begin-End boundary string" (2D B/spl epsi/-string) is proposed. The 2D B/spl epsi/-string represents an icon by its MBR boundaries. By applying a number of "dummy objects", the 2D B/spl epsi/-string can intuitively and naturally represent the pictorial spatial information without any spatial operator. In addition, an image similarity evaluation method based on the modified "Longest Common Subsequence" (LCS) algorithm is presented. By using the proposed evaluation method, not only can those images for which all the icons and their spatial relationships fully agree with the query image be sifted out, but also those images whose partial icons and/or spatial relationships are similar to the query image. It resolves the problems of query targets and/or spatial relationships not being certain. Our representation model and similarity evaluation also simplify the retrieval progress of linear transformations, including image rotation and reflection.
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