Content-based image retrieval using growing hierarchical self-organizing quadtree map

Authors:
Sitao Wu;M. K. M. Rahman;Tommy W. S. Chow
Affiliations:
Department of Electronic Engineering, City University of Hong Kong, Hong Kong;Department of Electronic Engineering, City University of Hong Kong, Hong Kong;Department of Electronic Engineering, City University of Hong Kong, Hong Kong
Venue:
Pattern Recognition
Year:
2005

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Abstract

In this paper, a growing hierarchical self-organizing quadtree map (GHSOQM) is proposed and used for a content-based image retrieval (CBIR) system. The incorporation of GHSOQM in a CBIR system organizes images in a hierarchical structure. The retrieval time by GHSOQM is less than that by using direct image comparison using a flat structure. Furthermore, the ability of incremental learning enables GHSOQM to be a prospective neural-network-based approach for CBIR systems. We also propose feature matrices, image distance and relevance feedback for region-based images in the GHSOQM-based CBIR system. Experimental results strongly demonstrate the effectiveness of the proposed system.