Content-based object organization for efficient image retrieval in image databases

被引:8
|
作者
Kwok, S. H.
Zhao, J. Leon
机构
[1] Calif State Univ Long Beach, Coll Business Adm, Dept Informat Syst, Long Beach, CA 90840 USA
[2] Hong Kong Univ Sci & Technol, Sch Business, Dept Informat & Syst Management, Kowloon, Hong Kong, Peoples R China
[3] Univ Arizona, Eller Coll Management, Dept Management Informat Syst, Tucson, AZ 85721 USA
关键词
blob-centric image representation; content-based image retrieval; image database management; MB+-trees; multi-dimensional indexing; object-oriented image organization;
D O I
10.1016/j.dss.2006.04.013
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Much research has focused on content-based image retrieval (CBIR) methods that can be automated in image classification and query processing. In this paper, we propose a blob-centric image retrieval scheme based on the blobworld representation. The blob-centric scheme consists of several newly proposed components, including an image classification method, an image browsing method based on semantic hierarchy of representative blobs, and a blob search method based on multidimensional indexing. We present the database structures and their maintenance algorithms for these components and conduct a performance comparison of three image retrieval methods, the naive method, the representative-blobs method, and the indexed-blobs method. Our quantitative analysis shows significant reduction in query response time by using the representative-blobs method and the indexed-blobs method. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1901 / 1916
页数:16
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