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Content-based object organization for efficient image retrieval in image databases [An article from: Decision Support Systems]
 
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Content-based object organization for efficient image retrieval in image databases [An article from: Decision Support Systems] [HTML] (Digital)

~ S.H. Kwok (Author), J.L. Zhao (Author)
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This digital document is a journal article from Decision Support Systems, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
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.

Product Details

  • Format: HTML
  • Printable: Yes
  • Mac OS Compatible: Yes
  • Windows Compatible: Yes
  • Handheld Compatible: Yes
  • Digital: 15 pages
  • Publisher: Elsevier (December 1, 2006)
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  • Required Free Software: Any web browser

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