文章基本信息

标题：http://computeroptics.smr.ru/KO/PDF/KO44-1/440117.pdf
本地全文：下载
作者：Yanxia Cai ; Yanyan Xu ; Dandan Li 等
期刊名称：Computer Optics / Компьютерная оптика
印刷版ISSN：0134-2452
电子版ISSN：2412-6179
出版年度：2020
卷号：44
期号：1
页码：137-141
DOI：10.18287/2412-6179-CO-630
语种：English
出版社：Samarskii Natsional'nyi Issledovatel'skii Universitet imeni Akademika S.P. Koroleva,Samara National Research University
摘要：This paper briefly introduces the optimal threshold calculation model and particle swarm optimization (PSO) algorithm for image segmentation and improves the PSO algorithm. Then the standard PSO algorithm and improved PSO algorithm were used in MATLAB software to make simulation analysis on image segmentation. The results show that the improved PSO algorithm converges faster and has higher fitness value; after the calculation of the two algorithms, it is found that the improved PSO algorithm is better in the subjective perspective, and the image obtained by the improved PSO segmentation has higher regional consistency and takes shorter time in the perspective of quantitative objective data. In conclusion, the improved PSO algorithm is effective in image segmentation.