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Proceedings Paper

Customized-queries approach to CBIR
Author(s): Jennifer G. Dy; Carla E. Brodley; Avinash C. Kak; Chi-Ren Shyu; Lynn S. Broderick
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Paper Abstract

This paper introduces a new approach called the 'customized- queries' approach to content-based image retrieval (CBIR). The customized-queries approach first classifies a query using the features that best differentiate the major classes and then customizes the query to that class by using the features that best distinguish the subclasses within the chosen major class. This research is motivated by the observation that the features which are most effective in discriminating among images from different classes may not be the most effective for retrieval of visually similar images within a class. This occurs for domains in which not all pairs of images within one class have equivalent visual similarity. We apply this approach to content-based retrieval of high-resolution tomographic images of patients with lung disease and show that this approach yields 82.8 percent retrieval precision. The traditional approach that performs retrieval using a single feature vector yields only 37.9 percent retrieval precision.

Paper Details

Date Published: 17 December 1998
PDF: 11 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333849
Show Author Affiliations
Jennifer G. Dy, Purdue Univ. (United States)
Carla E. Brodley, Purdue Univ. (United States)
Avinash C. Kak, Purdue Univ. (United States)
Chi-Ren Shyu, Purdue Univ. (United States)
Lynn S. Broderick, Univ. of Wisconsin Hospital (United States)


Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)

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