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Research on Image Segmentation Based on Improved Immune Genetic Algorithm

A problem with image segmentation during target extraction. In this paper, the immune genetic algorithm is used to realize image segmentation using MATLAB. By increasing the immune function, the method makes the genetic algorithm have a certain intervention in the process of crossover and mutation, and accelerates the solution speed, which is an improvement of the genetic algorithm. Through experimental comparison and analysis: in most cases, the results obtained by the immune genetic algorithm and the watershed algorithm are consistent. However, in some cases, the segmentation effect of the algorithm is better than the watershed algorithm. At the same time, the algorithm is faster than the watershed algorithm because of the introduction of immune operators. Immune genetic algorithm has important practical significance in image segmentation. The result of segmentation of the image preserves the boundary information of the image, which is more in line with the judgment result of human vision.