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Proceedings Paper

Finding regions of interest for content extraction
Author(s): Eric J. Pauwels; Greet Frederix
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Paper Abstract

A major problem in content based image retrieval (CBIR) is the unsupervised identification of perceptually salient regions in images. We contend that this problem can be tackled by mapping the pixels into various feature-spaces, whereupon they are subjected to a grouping algorithm. In this paper, we develop a robust and versatile non-parametric clustering algorithm that is able to handle the unbalanced and highly irregular clusters encountered in such CBIR applications. The strength of our approach lies not so much in the clustering itself, but rather in the definition and use of two cluster-validity indices that are independent of the cluster topology. By combining them, an optimal clustering can be identified, and experiments confirm that the associated clusters do, indeed, correspond to perceptually salient image regions.

Paper Details

Date Published: 17 December 1998
PDF: 10 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333869
Show Author Affiliations
Eric J. Pauwels, Katholieke Univ. Leuven (Belgium)
Greet Frederix, Katholieke Univ. Leuven (Belgium)

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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