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Proceedings Paper

Multilevel image segmentation and object representation for content-based image retrieval
Author(s): Pinar Duygulu; Fatos T. Yarman-Vural
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Paper Abstract

Due to the increasing demand and offer of the technology, the next generation of the image file formats will be more likely to store and retrieve images based on their semantic conte. Thus, an image should be segmented into 'meaningful' regions, each of which corresponds to an object and/or background. In this study, we propose a scheme for multi- level image segmentation, based on a simple descriptor, called 'the closest color in the same neighborhood'. The proposed scheme generates a stack of images without using any segmentation threshold. The stack of images is hierarchically ordered in a uniformity tree. The uniformity tree is then associated with a semantic tree, which is built by the user for content based representation. The experiments indicate superior results for retrieving images, which consist of few objects and a background.

Paper Details

Date Published: 1 January 2001
PDF: 10 pages
Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); doi: 10.1117/12.410956
Show Author Affiliations
Pinar Duygulu, Middle East Technical Univ. (Turkey)
Fatos T. Yarman-Vural, Middle East Technical Univ. (Turkey)

Published in SPIE Proceedings Vol. 4315:
Storage and Retrieval for Media Databases 2001
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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