Extracting color features and dynamic matching for image database retrieval

Color-based indexing is an important tool in image data-base retrieval. Compared with other features of the image, color features are less sensitive to noise and background complication. Based on the human visual system’s perception of color information, this paper presents a dependent scalar quantization approach to extract the characteristic colors of an image as color features. The characteristic colors are suitably arranged in order to obtain a sequence of feature vectors. Using this sequence of feature vectors, a dynamic matching method is then employed to match the query image with data-base images for a nonstationary identification environment. The empirical results show that the characteristic colors are reliable color features for image database retrieval. In addition, the proposed matching method has acceptable accuracy of image retrieval compared with existing methods.