A color indexing scheme using two-Level clustering processing for effective and efficient image retrieval

Zhang, Ji and Wang, Wei and Zhang, Sheng (2005) A color indexing scheme using two-Level clustering processing for effective and efficient image retrieval. In: 2005 International Conference on Data Mining (DMIN'05), June 2005, Las Vegas, Nevada, USA.

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Abstract

[Abstract]: In this paper, we present a clustering-based color indexing scheme for effective amd efficient image retrieval, which is essentially an exploration on the application of clustering technique to image retrieval. In our approach, the color features are clustered automatically using a color clustering algorithm twice (called two-level clustering processing) and two color feature summarizations are obtained, e.g. Local Color Centriods (LCCs) and Global Color Centroids (GCCs). Based upon LCCs and GCCs, a three-level R-tree is bulit for indexing database images and performing effecitve and efficient image retrieval. The experiments show that this indexing scheme is effective and efficient in performing image retrieval.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	No evidence of copyright restrictions.
Faculty / Department / School:	Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited:	25 Sep 2009 04:37
Last Modified:	02 Jul 2013 23:23
Uncontrolled Keywords:	image indexing and retrieval, clustering, data mining, R-tree
Fields of Research :	08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
URI:	http://eprints.usq.edu.au/id/eprint/5632

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