Region-Based Image Retrieval with Perceptual Colors

Due to the ‘semantic gap’ between low-level visual features and the rich semantics in user’s mind, performance of traditional contentbased image retrieval systems is far from user’s expectation. In attempt to reduce the ‘semantic gap’, this paper introduces a region-based image retrieval system with high-level semantic color names used. For each segmented region, we define a perceptual color as the low-level color feature of the region. This perceptual color is then converted to a semantic color name. In this way, the system reduces the ‘semantic gap’ between numerical image features and the richness of human semantics. Four different ways to calculate perceptual color are studied. Experimental results confirm the substantial performance of the proposed system compared to traditional CBIR systems.