小视场环境下的摄像机标定

摄像机标定旨在建立三维世界坐标与二维图像坐标之间的映射关系。传统标定板为数十个整齐排列的标准圆或网格,通过提取圆心坐标或网格角点坐标进行标定。在微小物体测量系统中,摄像机视场较小,无法从传统标定板提取足够多点坐标信息。针对这一问题,提出一种基于二次曲线与直线的混合标定方法。该方法抛弃了利用点对点关系的标定方法,转而利用二次曲线方程及直线方程在两种坐标系下相对应的关系进行标定,使摄像机即使是在非常小的范围内仍然能够提取足够的信息进行标定。仿真与实验证明,相对于基于点的标定方法,混合标定方法精度高,具有更好的稳健性。另外,标定模板为一个标准的半圆,制作简单,方便应用到小视场的环境中。

Camera Calibration under Small Field of View

Camera calibration aims at building up the mapping relationship between 3D world coordinate and 2D image coordinate. The traditional calibration board contains dozens of neatly arranged standard circles or grids. Calibration is completed by extracting the center coordinates of standard circles or grid corner coordinates. In a micro-object measurement system, the camera field of view is very small and camera cannot extract enough points from the calibration board. To solve this problem, a new method based on conic and lines is proposed. This method uses conic and lines equation instead of points to calibrate so that enough information can be extracted from calibration board even under small field of view. Both computer simulation and real data test show that the proposed method has higher accuracy and better robustness. In addition, the calibration board is a standard semicircle which is very easy to be made and easy to be used under small field of view.