中北大学学报（自然科学版）2018，Vol.39Issue(3)：355-361,7.DOI:10.3969/j.issn.1673-3193.2018.03.018
基于粒子群和蚁群算法的枪弹图像边缘检测方法
Bullet Image Edge Detection Based on Algorithm of Particle Swarm and Ant Colony
任雁 1李强 1张鹏军1
作者信息
- 1. 中北大学 机电工程学院,山西 太原030051
- 折叠
摘要
Abstract
Aiming at the defects such as slow convergence speed in the traditional edge detection of bullet images,a group optimization algorithm was proposed,which was an edge detection method for bullet image based on particle swarm optimization and ant colony optimization.The key was to combine the a-bove two algorithms together,so that the algorithm had both diversity and positive feedback.Firstly, PSO operation on the image was performed,and the sub-optimal solution of PSO was converted to the distribution of the initial pheromone for the following ACO after meeting the preset convergence condi-tions.Then ACO operation was performed.When ants were looking for food,diversity prevented the ants from going into an infinite loop.When the PSO reached a predetermined convergence condition, good positive feedback could be maintained.Finally,the bullet edge information of the image was shown.The experimental result proves that the hybrid algorithm proposed can extract clear bullet edges with complete details and profound and continuous edge information and that this algorithm works effec-tively in image edge detection.关键词
枪弹图像/边缘检测/蚁群算法/粒子群算法Key words
bullet image/edge detection/ant colony algorithm/particle swarm algorithm分类
信息技术与安全科学引用本文复制引用
任雁,李强,张鹏军..基于粒子群和蚁群算法的枪弹图像边缘检测方法[J].中北大学学报（自然科学版）,2018,39(3):355-361,7.
