<title>Color classification of color images based on uniform color spaces</title>

Abstract

The present paper describes a color classification method that partitions color image data into a set of uniform color regions. 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. First, the input image data are mapped from device coordinates into an approximately uniform perceptual color space. Colors are classified by means of cluster detection in the uniform color space. The 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 by the basic classification are reclassified on a color distance. The performance of the method is discussed in an experiment using a picture of paper objects.