Color histogram-based image segmentation

An algorithm is presented to segment a color image based on the 3D histogram of colors. The peaks in the histogram, i.e., the connected components of colors with locally maximal occurrence, are detected. Each peak is associated a representative color, which is the color of the centroid of the peak. Peaks are processed in decreasing occurrence order, starting from the peak with the maximal occurrence, with the purpose of maintaining only the representative colors corresponding to the dominant peaks. To this aim, each analyzed peak groups under its representative color those colors, present in the histogram and that have not been grouped to any already analyzed peak, such that their distance from the centroid of the peak is smaller than a priori fixed value. At the end of the grouping process, a number of representative colors, generally substantially smaller than the number of initial peaks, is obtained, which are used to identify the regions into which the color image is segmented. Since the histogram does not take into account spatial information, the image is likely to result over-segmented and a merging step, based on the size of the segmentation regions, is performed to reduce this drawback.