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In this paper, an optimized seeded region growing (SRG) image segmentation algorithm has been proposed. Here two stage swarm optimization has been used. The algorithm uses cat swarm optimization in first stage for selection of seed points and particle swarm optimization (PSO) in the second stage to determine the similarity criteria and assign the pixels to respective regions to perform image segmentation...
This paper proposes a new method for image segmentation using Cat Swarm Optimization (CSO) by multilevel thresholding. In the algorithm, each cat contains a set of threshold values that helps to get a given image partitioned into regions. The fitness value, position and velocity information of each cat is used to update the threshold values of each cat. The evaluation function deals with the segmented...
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