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Proceedings Paper

Quantization of color histograms using GLA
Author(s): Christopher C. Yang; Milo K. Yip
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Paper Abstract

Color histogram has been used as one of the most important image descriptor in a wide range of content-based image retrieval (CBIR) projects for color image indexing. It captures the global chromatic distribution of an image. Traditionally, there are two major approaches to quantize the color space: (1) quantize each dimension of a color coordinate system uniformly to generate a fixed number of bins; and (2) quantize a color coordinate system arbitrarily. The first approach works best on cubical color coordinate systems, such as RGB. For other non-cubical color coordinate system, such as CIELAB and CIELUV, some bins may fall out of the gamut (transformed from the RGB cube) of the color space. As a result, it reduces the effectiveness of the color histogram and hence reduces the retrieval performance. The second approach uses arbitrarily quantization. The volume of the bins is not necessary uniform. As a result, it affects the effectiveness of the histogram significantly. In this paper, we propose to develop the color histogram by tessellating the non-cubical color gamut transformed from RGB cube using a vector quantization (VQ) method, the General Loyld Algorithm (GLA) [6]. Using such approach, the problem of empty bins due to the gamut of the color coordinate system can be avoided. Besides, all bins quantized by GLA will occupy the same volume. It guarantees that uniformity of each quantized bins in the histogram. An experiment has been conducted to evaluate the quantitative performance of our approach. The image collection from UC Berkeley's digital library project is used as the test bed. The indexing effectiveness of a histogram space [3] is used as the measurement of the performance. The experimental result shows that using the GLA quantization approach significantly increase the indexing effectiveness.

Paper Details

Date Published: 30 August 2002
PDF: 8 pages
Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); doi: 10.1117/12.481607
Show Author Affiliations
Christopher C. Yang, Chinese Univ. of Hong Kong (Hong Kong)
Milo K. Yip, Chinese Univ. of Hong Kong (Hong Kong)

Published in SPIE Proceedings Vol. 4925:
Electronic Imaging and Multimedia Technology III
LiWei Zhou; Chung-Sheng Li; Yoshiji Suzuki, Editor(s)

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