A color classification method for color images using a uniform color space

A color classification method that partitions color image data into a set of uniform color regions is described. The ability to classify spatial regions of the measured image into a small number of uniform regions can be useful for several problems, including image segmentation and image representation. The input image data are first mapped from device coordinates into all approximately uniform perceptual color space. Colors are classified by means of cluster detection in the uniform color space. The classification process is composed of two stages of basic classification and reclassification. The basic classification is based on histogram analysis to detect color clusters sequentially. The principal components of the color data are extracted for effective discrimination of clusters. At the reclassification stage, the extracted representative colors are reclassified on a color distance. Experimental results show that a fundamental set of colors composing an image with shades and shadows is extracted at the basic classification stage and that the objects in the original image are extracted at the reclassification stage.>