Camera calibration

which is to calculate the intrinsic and extrinsic parameters of a camera in viewing

is one of the basic tasks for analyzing the geometry of a scene and determining the shapes and locations of objects in vision. Since the optical system of a real camera has many types of distortions

and these distortions must be taken into account in three dimensional geometry reconstruction when high precision is needed

this will cause the relation of perspective transformation to be nonlinear. Many efforts have been made to solve the nonlinear calibration problem. A new linear three-step approach for camera calibration was proposed to deal with camera model of one order radial distortion. In the first stage all extrinsic parameters except those for translation vector in Z-axis are computed by using the Radial Parallelism Constraint(RAC). In the second stage the one order radial distortion parameter is computed by using cross ratio invariability. In the third stage all the missing parameters are computed by the least square method. Experiments with simulated data as well as real image show that the new approach is efficient

robust and accurate. And the approach eliminates the nonlinear iterative calculation processes.