摘要
Abstract
In view of the existing problem of insufficient accuracy and low efficiency in mine used instruments and meters image segmentation,a multi-strategy improved dung beetle algorithm(Z-DBO)is proposed.This algorithm enhances population diversity through Chebyshev chaotic mapping initialization,improves global search capability through golden sine strategy,and prevents premature convergence through Levy flight mechanism.The experiment verifies that the Z-DBO algorithm performs excellently on 16 standard test functions,with significantly improved convergence speed and optimization ability compared to SSA,PSO,and the original DBO.When applied to the image segmentation of mine used instruments and meters,the Z-DBO algorithm not only significantly reduces the fitness value(reduced by 40.9%,9.7%,26%compared to PSO,SSA,and DBO,respectively),but also significantly reduces the number of iterations(reduced by 9%,54%,25%,respectively),effectively improving the accuracy and efficiency of image segmentation,and verifying the innovativeness and practicality of Z-DBO combined with k-means in mine used instruments and meters image processing.关键词
蜣螂算法/Chebyshev混沌映射/黄金正弦策略/莱维飞行机制/图像分割Key words
dung beetle algorithm/Chebyshev chaotic mapping/golden sine strategy/Levy flight mechanism/image segmentation分类
信息技术与安全科学
