MCEBC – A blob coloring algorithm for content-based image retrieval system

Abstract

In most content-based image retrieval systems, colors are used as very significant feature for indexing and retrieval purposes. Many of them use the quantized colors for various reasons. In some systems, especially the systems accepting user-drawn queries, color quantization improves the overall performance as well as the execution time. In this paper, a new color quantization method, which uses some heuristics to minimize the color matching errors, is proposed. The proposed MCEBC(Main Color Emphasized Blob Coloring) algorithm quantizes the colors into the predefined color classes, using the heuristic information that humans tend to emphasize the dominant color component when they perceive and memorize colors. The experimental results indicate that the proposed method approximates the user’s classification better than the other methods that use the mathematical color difference formulas. The proposed MCEBC algorithm is implemented in a content-based image retrieval system, called QBM system. The retrieval results of the system using MCEBC algorithm were quite satisfactory and showed higher success rates than those using other methods.