针对传统摄像机标定算法中摄像机内外参数与镜头畸变之间存在耦合，提出了一种将镜头畸变从摄像机参数中分离出来单独求解的算法。算法基于“三维空间中的直线经过遵循透视模型的相机投影，在相机平面上仍是直线”这一基本属性。对于无畸变图像，直线上任意两特征点构成的共线向量外积应为零向量。利用非线性优化方法求解畸变参数，讨论了畸变中心与畸变系数之间的耦合性。设计了一种畸变校正效果评估方法，证明了结果的正确性。完成畸变校正后，摄像机的内外参数可线性求解。实验表明，该方法仅需一张图片即可完成所有摄像机参数的求解，提高了标定效率，且稳定度高，精度与传统标定方法相当。

Lens distortion is coupled with intrinsic and extrinsic camera parameters in traditional camera calibration algorithms. An algorithm which separates lens distortion from camera parameters is proposed. The algorithm is based on the fundamental property that a camera follows the perspective camera model if and only if the projection of every three dimensional (3D) line in space onto the camera plane is a line. For undistorted images, the cross product of collinear vectors which consist of any two feature points on a line should be a zero vector. Distortion parameters are found by using nonlinear optimization algorithms and the coupling between distortion center and distortion coefficient is also discussed. An evaluation method for the effect of distortion correction is designed so as to prove the correctness of the proposed algorithm. Once distortion correction is completed, intrinsic and extrinsic camera parameters can be solved linearly. The experimental results indicate that the proposed algorithm can implement the solving of all camera parameters by using only one calibration image. As a result, the efficiency of calibrating is improved. Moreover, the proposed algorithm performs more stably and has nearly the same accuracy as traditional methods.