The capability of extracting and recognizing characters printed in color documents will widen immensely the applications of OCR systems. This paper describes a new method of color segmentation to extract character areas from a color document. At first glance, the characters seem to be printed in a single color, but actual measurements reveal that the color image has a distribution of components. Compared with clustering algorithms, our method prevents oversegmentation and fusion with the background while maintaining real-time usability. It extracts the representative colors based on a histogram analysis of the color space. Our method also contains a selective local color averaging technique that removes the problem of mesh noise on high-resolution color images.