A displacement measurement method for micro vision system based on fast block matching with particle swarm optimization algorithm
Displacement measurement is crucial in a micro vision system with applications to micro positioning stages.To address the problem of expensive time consumption in real computations,this paper presents an efficient method based on fast block matching(BM)with particle swarm optimization(PSO)algorithm.In this method,the pinhole imaging model for the system as well as the corresponding Jacobin matrix is firstly estimated; then,a fast BM algorithm is performed to measure to displacement of the micro positioning stage where the matching level of two candidate blocks in two different frames are quantified by using the sum of absolute differences(SAD).In particular,to speed up the matching process,an improved Particle Swarm Optimization algorithm is proposed in this paper,in which new iterative strategy is adopted to locate an approximate successfully-matching region and a fully-searching algorithm(FSA)is operated next to reach the final result.Experimental results demonstrated excellent performances on computation speed and measurement accuracy,which suggests good potentials of the method in real applications.
high accuracy measuring block matching PSO micro positioning stage micro vision
Zhu Yongbo Lu Guoliang Peng Yan
Key Laboratory of High Efficiency and Clean Mechanical Manufacture of MOE,Jinan,China School of Mechanical Engineering,Shandong University,Jinan,China
国际会议
第十七届国际制造会议(The 17th International Manufacturing Conference in China)(IMCC 2017))
深圳
英文
1-10
2017-11-23（万方平台首次上网日期，不代表论文的发表时间）