现代电子技术2018，Vol.41Issue(10)：81-84,89,5.DOI:10.16652/j.issn.1004⁃373x.2018.10.021
一种新的粒子群优化的图像匹配算法
A new image matching algorithm based on particle swarm optimization
摘要
Abstract
In allusion to the problems that the particle swarm algorithm is prone to fall into local optimum,and has slow searching speed and low matching precision in image matching,a new image matching algorithm based on particle swarm optimi-zation is proposed. The particle swarm algorithm is optimized by using the improved nonlinear inertia weight to balance the glob-al and local searching capability of particles. The addition of the dynamic disturbance term is proposed to disturb the velocity so that the local optimum can be avoid when the velocity of particles falls to zero at the later stage of the algorithm. The simulation results show that this algorithm can improve the global searching capability and convergence precision of particles which can ef-fectively prevent the premature phenomenon,and has the characteristics of faster convergence speed,better robustness,and higher matching precision in comparison with the standard PSO image matching algorithm.关键词
图像匹配/粒子群算法/惯性权重/速度扰动/搜索速度/收敛精度Key words
image matching/particle swarm algorithm/inertia weight/velocity disturbance/searching speed/convergence precision分类
信息技术与安全科学引用本文复制引用
王长清,朱进进,张佳伟..一种新的粒子群优化的图像匹配算法[J].现代电子技术,2018,41(10):81-84,89,5.基金项目
河南省科技攻关项目(162102210072)Project Supported by Science and Technology Breakthrough Project of Henan Province(162102210072) （162102210072）
