基于主动视觉的摄像机自标定是摄像机标定的一个重要分支，由于普通的 CCD摄像机拍摄的像片存在着各种类型的几何畸变，其中以径向畸变最为严重，因此研究考虑径向畸变的自标定技术有着重要的意义.为了使标定结果更精确，提出了一种考虑二阶径向畸变的内参数自标定方法，并通过推导考虑二阶径向畸变的极线几何约束，得出了如果能控制摄像机做 4次不在同一平面上的平移运动，则可以标定摄像机的内参数和二阶径向畸变系数的结论.仿真实验结果表明，该算法精度很高，且具有一定的鲁棒性，可用于摄像机的标定.

Camera self-calibration techniques based on active vision make the calibration simplified, so it is a main branch of camera calibration field. Many kinds of distortions were existed in ordinary camera, among these distortions the radial distortion is more serious, so the study on the self-calibration technique taking account of radial distortion is very important. A camera self-calibration algorithm based on active vision taking account of two-degree radial distortion is proposed in this paper in order to make the calibration result more accurate. The epipolar geometry constraint taking account of two-degree radial distortion is developed. Then the conclusion was drawn that the epipole of the image which is taken after the translation motion is done is still equal to the epipole of the initial position image when the two-degree radial distortion is taken account. The calibration taking account of two-degree radial distortion become a problem to solve complex nonlinear equations. The Levenberg-Marquardt algorithm is used to solve the nonlinear equations. Then the intrinsic parameters and two-degree radial distortion coefficients can be calibrated by controlling the camera to undergo four translations or more which should not be co-planar. Experiments results show that the accuracy of the algorithm is high and the robustness of the algorithm is strong. So this algorithm is feasible.