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.