| 图像检索中的相似性判别及索引方法综述 |
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| 引用本文： | 于林森,张田文,张开越.图像检索中的相似性判别及索引方法综述[J].小型微型计算机系统,2007,28(2):356-360. |
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| 作者姓名： | 于林森 张田文 张开越 |
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| 作者单位： | 1. 哈尔滨工业大学,计算机科学与技术学院,黑龙江,哈尔滨,150001
2. 哈尔滨工业大学,软件学院,黑龙江,哈尔滨,150001 |
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| 摘 要： | 基于内容的图像检索(CBIR)是对传统信息检索领域的扩展.它采用图像视觉内容的相似性判别进行查询.CBIR涉及到很多科学领域的课题.本文则仅主要综述CBIR技术中的相似性度量方法,索引方式,以及检索性能的评价.最后,分析了该领域现存的问题、最新研究动态及发展方向.
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| 关 键 词： | 图像检索 相似性度量 高维索引 性能评价 |
| 文章编号： | 1000-1220（2007）02-0356-05 |
| 修稿时间： | 2005-11-16 |
Review of Indexing Methods for Image Retrieval |
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| YU Lin-sen,ZHANG Tian-wen,ZHANG Kai-yue.Review of Indexing Methods for Image Retrieval[J].Mini-micro Systems,2007,28(2):356-360. |
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| Authors: | YU Lin-sen ZHANG Tian-wen ZHANG Kai-yue |
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| Affiliation: | 1 Computer Science and Technology College, Harbin Institute of Technology, Harbin 150001, China; 2 School of Software, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: | Content Based Image Retrieval(CBIR)is an extension to the traditional information retrieval. It adopts visual content rather than keyword to judge image similarity. CBIR systems involve a broad area of scientific research. This paper only gives a comprehensive survey of similarity measurement, feature organization and access methods, and performance evaluation in CBIR. Finally, the survey analyses the open issues, research trends and promising directions in this area. |
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| Keywords: | image retrieval similarity measure high-dimensional indexing performance evaluation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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