Image segmentation using improved genetic algorithm

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Abstract

Segmentation of image is a complex task. To recognize an image, segmentation is essential parts. During image segmentation, subsets of images on the basis of some features like gray levels values of pixels or position of pixels find out. This is an NP-complete problem, to find the solution to such problems is a computationally hard task. Some heuristic algorithm can be used to find out the solution to such a hard task. These algorithms find approximate solutions. Exact solution of such problems is not possible. Genetic algorithm can be considered a metaheuristic algorithm used the evolution of the population of solutions. This paper proposedan improved Genetic Algorithm that used to find multi-level thresholding segmentation of the image. The threshold value can be calculated by cumulative histogram and satisfactory result have been given by the experiments done on test images that are taken from Mnist datasets.

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Kumari, R., Gupta, N., & Kumar, N. (2019). Image segmentation using improved genetic algorithm. International Journal of Engineering and Advanced Technology, 9(1), 1784–1792. https://doi.org/10.35940/ijeat.F9063.109119

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