In this paper, we propose a method for extracting color image features, called color index local auto-correlations. Pixel color is quantized and described sparsely in a manner similar to the color indexing of color histograms. In addition, by utilizing spatial auto-correlations of the color indexes, the characteristics of color texture can be extracted more effectively than ordinary histogram-based methods. The proposed method has variants in terms of the color space and basic colors used for indexing colors. These various settings are comprehensively compared in the experiments of image retrieval and image classification, and are shown to exhibit favorable results compared to the other conventional methods.
['Takumi Kobayashi', 'Nobuyuki Otsu']
Color image feature extraction using color index local auto-correlations