A planar constraint optimization method to improve camera calibration for imperfect planar targets

Camera calibration is a crucial step in vision-based measurement systems. However, the accuracy of camera calibration is affected by the imprecise calibration targets. To remedy the deviations caused by imperfect planar targets, a planar constraint optimization method is proposed to improve camera calibration on the basis of a virtual perfect plane deviation model. This method allows us to correct the target geometry within a truth scale factor. Specifically, we add deviation parameters for each feature point on the target relative to a virtual perfect plane, which is used to describe the machining errors. Those deviation parameters will be optimized together with the calibration parameters of the camera to correct the feature points' position and improve calibration accuracy. Both simulation and real experiments have demonstrated that the proposed method can attain high-precision calibration results and measurement accuracy comparable to those with traditional method and a precise target, even using an imperfect target.