基于麻雀搜索算法的摄像机标定优化方法  

Camera Calibration Optimization Method Based on Sparrow Search Algorithm

作　　者：张宏峰 倪受东[1] 赵亮 张猛 Zhang Hongfeng;Ni Shoudong;Zhao Liang;Zhang Meng(School of Mechanical and Pouwer Engineering,Nanjing Tech University,Nanjing,J iangsu 211816,China)

机构地区：[1]南京工业大学机械与动力工程学院,江苏南京211816

出　　处：《激光与光电子学进展》2021年第22期376-382,共7页Laser & Optoelectronics Progress

基　　金：江苏省科技厅政策引导计划(产学研合作)/前瞻性联合研究项目(BY2016005-05)。

摘　　要：针对传统摄像机标定方法标定精度低且标定可重复性差等问题,提出了一种基于麻雀搜索算法(SSA)的摄像机标定方法。首先,利用MATLAB软件中的标定工具箱,获得摄像机内参和外参的初估值,并以求出的初估值为基础,确定SSA的运行区间。然后,通过建立平均重投影误差方程,利用SSA对确定区间内的摄像机参数进行优化,获得了较小的平均重投影误差。最后,将所提标定方法与基于天牛须搜索算法、粒子群优化算法的标定方法的结果进行对比分析,发现利用基于SSA的摄像机标定方法所得的平均重投影误差最小(0.0326 pixel)且方法的可重复性最好。To solve the problems of low calibration accuracy and poor repeatability of traditional camera calibration methods,a camera calibration method based on sparrow search algorithm(SSA)is proposed.Firstly,the initial values of internal and external parameters of the camera are obtained by using the calibration toolbox in MATLAB software,and the running interval of SSA is determined based on the initial estimates.Then,the camera parameters in the determined interval are optimized by SSA,and a small average reprojection error is obtained.Finally,the results of the proposed calibration method are compared with those of calibration methods based on beetle antennae search algorithm and particle swarm optimization algorithm.It is found that the average reprojection error of the camera calibration method based on SSA is the smallest(0.0326 pixel)and the repeatability of the method is the best.

关 键 词：机器视觉 摄像机标定 摄像机模型 内部参数 畸变系数 麻雀搜索算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]