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Proceedings Paper

Analysis of multilevel color histograms
Author(s): Raymond T. Ng; Dominic Tam
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Paper Abstract

Color is one of the most recognizable elements of image content, and color histogram is the most commonly used technique for indexing colors. Faloutsos et al. propose using a 3D index to perform histogram filtering. Sawhney and Hafner later generalize the filtering approach by using k- dimensional indices. The main contribution of this paper is the development and analysis of multi-level color histograms. The key idea is to insert additional levels of abstracted histograms in between a low dimensional index and the original histograms. Based on a cost model we developed, our analysis shows that in most cases, the optimal 3-level and 4-level configurations, when compared with the Faloutsos configuration and the optimal Sawhney-Hafner configuration, require lower CPU and I/O costs. Experimental results indicate that the gain in total time can vary from 22% to 400%. Our analysis also shows that the overhead required by 3-level and 4-level histograms is negligible.

Paper Details

Date Published: 15 January 1997
PDF: 12 pages
Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); doi: 10.1117/12.263420
Show Author Affiliations
Raymond T. Ng, Univ. of British Columbia (Canada)
Dominic Tam, Univ. of British Columbia (Canada)

Published in SPIE Proceedings Vol. 3022:
Storage and Retrieval for Image and Video Databases V
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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