Open AccessThreshold image target segmentation technology based on intelligent algorithms
Author(s) -
Yanxia CAI,
Yanyi Xu,
T. R. Zhang,
D. D. Li
Publication year - 2020
Publication title -
kompʹûternaâ optika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.491
H-Index - 29
eISSN - 2412-6179
pISSN - 0134-2452
DOI - 10.18287/2412-6179-co-630
Subject(s) - particle swarm optimization , image segmentation , matlab , algorithm , segmentation , consistency (knowledge bases) , perspective (graphical) , computer science , image (mathematics) , segmentation based object categorization , scale space segmentation , artificial intelligence , operating system
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.