A Region-Based SRG Algorithm for Color Image Segmentation

In this paper, we present an automatic seeded region growing (SRG) algorithm for color image segmentation. The method uses regions rather than pixels as the seeds of SRG. The architecture of the algorithm can be described as follows. First, the input RGB color image is transformed into HSI color space. Second, we use watershed segmentation to initialize the image. Third, the initial region seeds are automatically selected according to two rules advanced by us. Fourth, the color image is segmented into regions. Finally, region-merging method is used to merge similar or small regions. Compared with pixel-based SRG algorithm, our method can yield more robust and precise results. Experimental results have also shown that our algorithm can produce excellent results.