计算机与现代化 ›› 2022, Vol. 0 ›› Issue (03): 76-81.

• 图像处理 • 上一篇    下一篇

线阵相机的圆环旋转标定方法

  

  1. (1.武汉科技大学机械自动化学院,湖北武汉430080;2.武汉科技大学信息科学与工程学院,湖北武汉430080)
  • 出版日期:2022-04-29 发布日期:2022-04-29
  • 作者简介:田忠(1994—),男,湖北荆门人,硕士研究生,研究方向:机器视觉,图像处理,E-mail: 508398622@qq.com; 伍世虔(1964—),男,江西赣州人,教授,博士生导师,研究方向:机器视觉,智能机器人,图像处理。
  • 基金资助:
    国家自然科学基金资助项目(61775172); 武汉科技大学重大科技培育类项目(2018TDX06)

Rotation Calibration Method of Concentric Circles for Line Scan Camera

  1. (1. School of Mechanical Automation, Wuhan University of Science and Technology, Wuhan 430080, China;

    2. School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430080, China)
  • Online:2022-04-29 Published:2022-04-29

摘要: 由于传统线阵相机的标定过程复杂,且对标定物精度要求较高,难以保证缺陷的定位精度,本文提出一种线阵相机的圆环旋转标定方法以提高缺陷的定位精度。该方法设计一种新型的圆环形标定板,在静态标定基础上通过旋转线阵相机采集相机视线与圆的交点的坐标,得到旋转角度以及多组标定点,建立线阵相机的成像模型和径向畸变模型,通过非线性优化整体误差函数求解相机的内参和畸变参数,同时分析相机不同旋转角度对标定精度的影响。实验结果表明,当θ≤20°时,该方法的标定精度在0.35 pixel以内,满足实际检测的定位要求,并且在PCB缺陷检测中得到较好的验证。

关键词: 线阵相机标定, 圆环形标定, 非线性优化, 成像模型, 标定误差

Abstract: The calibration process of traditional line scan cameras is complex and requires high accuracy of calibration objects, it is difficult to ensure the positioning accuracy of defects. This paper proposes a ring rotation calibration method for line scan cameras to improve the positioning accuracy of defects. This method designs a new type of circular calibration board. On the basic of static calibration, the coordinates of the intersection of the camera’s line of sight and the circle are collected by a rotating line camera to obtain the rotation angle and multiple sets of calibration points to establish the imaging model and radial distortion model of the line camera. The internal parameters and distortion parameters of the camera are solved by nonlinear optimization of the global overall function, and the impact of different camera rotation angles on the calibration accuracy are analyzed. The experimental results show that when θ≤20°, the calibration accuracy of this method is within 0.35 pixel, which meets the positioning requirements of actual detection. The PCB defect detection is well verified.

Key words: linear camera calibration, circular calibration board, nonlinear optimization, imaging model, calibration error