Application of Seeded Region Growing to Color Image Segmentation
A color image segmentation method is presented based on the SRG method. Seeds can be automatically selected in the L*a*b* color space by making use of both color differences and relative Euclidean distances in the new algorithm; the new methods of SRG is used to form the initial segmented regions; and the initial regions are hierarchically merged based on the region distance defined by the color spatial and adjacent information. The proposed algorithm can overcome the disadvantages of not selecting seeds automatically and leading to the result of over-segmented by the traditional SRG method. And it can be applied to color image segmentation successfully. The meaningful experiment results of color image segmentation hold favorable consistency in terms of human perception and have shown feasibility and effectiveness to various natural color images.