摘要
针对工业环境下拍摄的大视场图像受噪声与畸变影响较大,使用传统匹配参数计算方法的精度无法满足现场测量需求的问题,提出一种基于非度量校正的大视场图像匹配参数标定算法。设计了一种共线特征点布置方案,基于非度量校正完成了特征点坐标的畸变校正,并提出基于该布置方案的特征点识别匹配算法,通过分区域抽样一致性法实现匹配参数的高精度标定。实验结果表明,该算法匹配精度相较于传统方法提高了51%以上,能够满足工业环境下大视场图像匹配参数所需的精度要求。
In order to solve the problem that images shot under industrial environment is considerably influenced by noise and distortion,precision of traditional algorithms for calibrating matching parameters cannot meet field measurement demand,a new method for calibrating large field of view image matching parameters based on nonmetric correction is proposed.A layout plan of colinear feature points is designed,and based on non-metric correction,image coordinates of colinear feature points can be undistorted,which can be recognized and matched automatically with the aid of layout plan.Modified random sampling consensus algorithm based on regional division is proposed,and matching parameters can be calibrated.Experimental results show that matching precision is increased by 51%at least,which meets precision requirements under industrial environment.
作者
张致远
刘巍
张洋
逯永康
邸宏图
叶帆
贾振元
Zhang Zhiyuan;Liu Wei;Zhang Yang;Lu Yongkang;Di Hongtu;Ye Fan;Jia Zhenyuan(School of Mechanical Engineering,Dalian University of Technology,Dalian,Liaoning 116024,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2018年第8期60-67,共8页
Acta Optica Sinica
基金
国家973计划(2014CB046504)
国家自然科学基金优秀青年科学基金项目(51622501)
国家自然科学基金创新研究群体项目(51621064)
关键词
机器视觉
视觉测量
匹配参数
大视场
非度量校正
machine vision
vision measurement
matching parameter
large field of view
non-metric correction
