From a theoretical standpoint, meaningful region segmentation based only on gray level or color usually presents over
segmentation or non-continuous regions. In view of this, we adopt a number of classical powerful algorithms (mean shift
clustering, edge detection and region growing) to extract the meaningful regions adds spatial information. These
algorithms are subjectively connected together and impact the results each other. The experiments indicate that the
proposed method can avoid over-segmentation phenomenon and the results can be easily accepted by human eyes.
Experimental results are superior to that of kmeans clustering method in both real-time performance and image
segmentation performance. Finally, we achieved a new procedure to extract meaningful regions by clicking some place
of a color image. It possesses a good application prospect and owns an effective real-time performance.