A high accuracy camera calibration for vision-based measurement systems

An important task in most 3D measurement systems based on machine vision is camera calibration, whose objective is to estimate the internal and external parameters of each camera. A new accurate calibration method with multilevel process of camera parameter is presented. Flexibly making use of geometry imaging theory, our algorithm obtain all the parameters through logical organization of solving order, accordingly avoid obtaining possible local optimized problem when solving the non-linear equation. The camera model is aimed at efficient computation of camera extrinsic and intrinsic parameters considering lens distortion, which are solved dividedly. Built on strict geometry constraint, our calibration method gets over the relativity influence of every unknown parameters of traditional calibration way, and makes the error distributed among the constraint relation of parameters, in order to guarantee the accuracy. Experimental results are provided to show that the accuracy is high.