A color image segmentation methodology based on a self-organizing map (SOM) is proposed. The method developed takes into account the color similarity and spatial relationship of objects within an image. According to the features of color similarity, an image is first segmented into coarse cluster regions. The resulting regions are then treated by computing the spatial distance between any two cluster regions, and the SOM with a labeling process is applied. In this paper, the selection of the parameters for the SOM algorithm was also investigated experimentally. The experimental results show that the proposed system is feasible, and that the segmented object regions are similar to those perceived by human vision.