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Proceedings Paper

Seeded image segmentation for content-based image retrieval application
Author(s): Jianping Fan; Mathurin Body; Xingquan Zhu; Mohand-Said Hacid; Essam A. El-Kwae
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Paper Abstract

Seeded image growing (SRG) algorithm is very attractive for semantic image segmentation but it also suffer from the problems of pixel sorting orders for labeling and automatic seed selection. We design an automatic SRG algorithm, along with a boundary-oriented parallel pixel labeling technique and an automatic seed selection method. In order to support more efficient image access over large-scale database, we suggest a multi-level image database management structure. This framework also supports a concept-oriented image classification via a probabilistic approach. Hierarchical image indexing and summarization are also discussed.

Paper Details

Date Published: 19 December 2001
PDF: 12 pages
Proc. SPIE 4676, Storage and Retrieval for Media Databases 2002, (19 December 2001); doi: 10.1117/12.451087
Show Author Affiliations
Jianping Fan, Univ. of North Carolina/Charlotte (United States)
Mathurin Body, Univ. Claude Bernard Lyon I (France)
Xingquan Zhu, Purdue Univ. (United States)
Mohand-Said Hacid, Univ. Claude Bernard Lyon I (United States)
Essam A. El-Kwae, Univ. of North Carolina/Charlotte (United States)


Published in SPIE Proceedings Vol. 4676:
Storage and Retrieval for Media Databases 2002
Minerva M. Yeung; Chung-Sheng Li; Rainer W. Lienhart, Editor(s)

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