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egmentation is one of the important steps for image analysis. Multilevel thresholding image segmentation was more popular in image segmentation. Otsu and Kapur based methods are most popular for multilevel threshold image segmentation. Many authors implemented evolutionary algorithms for the optimal multilevel threshold selection based on the above methods. In this paper, an efficient approach for multilevel image segmentation has been proposed and implemented based on novel evolutionary algorithm Improved Differential Search (IDS). The feasibility of proposed approach/algorithm has been tested on standard gray scale images. To check the effectiveness of the proposed approach/algorithm, all experimental results are analyzed quantitatively and qualitatively

An efficient approach for optimal multilevel thresholding selection for gray scale images based on improved differential search algorithm