轮廓测量系统中摄像机的光学畸变校正方法

在基于机器视觉的轮廓测量系统中，由于摄像机的透镜透光率不均，成像中存在光学畸变，对测量精度造成影响。为了对光学畸变进行校正，论文首先建立畸变数学模型，然后使用系统测量正方形标定板得到存在畸变的轮廓数据，根据存在畸变的轮廓数据的几何特征和直线约束条件使用LM优化算法完成对畸变模型中参数的标定。通过实验多次标定同一套轮廓测量系统，将标定结果与已有方法进行比较。实验结果表明，相较于已有算法，该论文所提方法多次标定的结果标准差更小，说明该论文所提方法具有更好的鲁棒性。

Optical distortion correction method for cameras in contour measuring system

In the contour measurement system based on machine vision, optical distortion exists in the imaging due to the uneven lens transmittance of the camera, which affects the measurement accuracy. In order to correct the optical distortion, the distortion mathematical model is firstly established, and then the distorted contour data is obtained by measuring the square calibration plate. According to the geometric characteristics of the distorted contour data and the linear constraint conditions, the parameters in the distortion model are calibrated by using LM optimization algorithm. The same contour measurement system was calibrated several times by experiments and the calibration results were compared with the existing methods. The experimental results show that the standard deviation of the proposed method is smaller than that of the existing algorithms, which indicates that the proposed method has better robustness.