Content-based color quantization and texture extraction for image indexing

A novel method of color and texture feature extraction for image retrieval is proposed. First, an input image is divided into 4×4 nonoverlapping blocks. Then, each block is quantized into two colors by color moment preserving and merging similar colors according to their color difference values under a preset threshold value. A few dominant colors are obtained, and a color histogram of the reconstructed image is computed for the color feature. For the texture feature, by preserving some color moments in the 4×4 neighborhood of each pixel, a bitmap is generated, which can be matched with 64 predefined bitmaps. Then a bitmap spectrum is obtained by counting bitmaps frequencies when all pixels of the input image are considered. An efficient method of similarity measurement is also presented. Experimental results show the proposed method performs well in terms of precision and recall.