In this paper a new method for color image segmentation is presented. The proposed algorithm divides the image into homogeneous regions by derivation of local thresholds via local information. The algorithm contains two main steps. First, the watershed algorithm is applied on the image gradient magnitude. Its results are used as an initial segmentation for the next step, which is region merging process. During that process regions are merged and local thresholds are derived one-by-one at different times by analyzing local characteristics of the regions. Every threshold refers to specific region and defines it as i final regioni (non-mergeable). Thus, regions are handled separately; some regions grow while others were already defined as i final regionsi. The significant use of local information improves the quality of the segmentation result. Experimental results have demonstrated the efficiency of the proposed method. The algorithm is found to be reliable and robust for different images.
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