大倾角靶标的双目相机高精度标定方法

High-Precision Calibration Method of Binocular Cameras for Large Inclination Targets

相机标定的精度是决定视觉测量精度的关键。针对标定过程中的倾角检测能力不足、标定精度低等问题,提出了一种面向大倾角靶标图的双目相机标定方法。通过聚类靶标标识点的几何特征数据,设计了无先验阈值参数的标识点提取算法,以提高大倾角靶标图的检测能力;同时,根据无倾斜角的理想靶标平面图与倾角靶标图的匹配相关性,提出了采用标识点的局部形变匹配代替直接检测法的思路。通过求解最优化的局部形变参量来近似求解投影偏差,从而提高真实圆心的检测精度。仿真和实验结果显示,相较于现有方法,本文标定方法的倾角检测能力得到显著提升。仿真图的标定精度的最大提升幅度为82%,实验标定图的标定精度的最大提升幅度为60%。

Camera calibration accuracy determines the precision of vision-based measurement.To address the issues of limited inclination angle detection and low calibration accuracy,this paper proposes a binocular camera calibration method for target images with large inclination angles.By clustering the geometric feature data of target marked points,the paper designs a marked point extraction algorithm without prior threshold parameters to enhance the capability of detecting target images with large inclination angles.Meanwhile,the paper uses local deformation matching of marked points to replace direct detection according to the matching correlation between the ideal target plane images without inclination angles and target images with inclination angles.In addition,in order to improve the detection accuracy of the real circle center,the projection deviation is estimated by calculating the optimal local deformation parameter.Simulation and experimental results demonstrate that the proposed calibration method is more sensitive in detecting inclination angles than the traditional method.The calibration accuracy for the simulation images is improved by up to 82%,and that for experimental calibration images is enhanced by up to 60%.