A Multi-level Thresholding for Image Segmentation using Improved PSO Algorithms
Abstract
Image is a collection of pixel or voxel which is used to manipulate and analyze the consisting data in digital format. Processing of an image is done to improve the quality and magnify the required data. In the proposed method, threshold based image segmentation is used in which multi-level thresholding is done to carry out multiple thresholds values of a single image which is performed by maximizing the objective function. Here different variants of PSO i.e., Particle swarm optimization (PSO), Darwinian PSO (DPSO), Fractional-order Darwinian particle swarm optimization (FO-DPSO) is used on gray scale images to improve the quality, CPU time and find the optimal threshold value
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