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

Authors:
S. H. Kwok;J. Leon Zhao
Affiliations:
Dept. of Inform. Sys., Col. of Bus. Admin., California Ste. Univ., Long Beach, Long Beach, CA and Dept. of Inform. and Sys. Mgmt., HKUST Bus. Sch., Hong Kong Univ. of Sci. and Technol., Clear Wate ...;Dept. of Inform. and Sys. Mgmt., HKUST Bus. Sch., Hong Kong Univ. of Sci. and Technol., Clear Water Bay, Kowloon, Hong Kong SAR, China and Dept. of Mgmt. Inform. Sys., Eller Col. of Mgmt., The Uni ...
Venue:
Decision Support Systems
Year:
2006

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Abstract

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.