Industrial Binocular Vision System Calibration With Unknown Imaging Model

The high precision measurement of binocular camera depends on the calibration accuracy. Mainstream methods focus on the calibration of intrinsic parameters and the pose relationship of two cameras in sequence. However, the transmission of error will decrease the calibration quality. It is still challenging especially in the case of an unknown imaging model due to the intervention of baffle and multimedia refraction. In this article, a general calibration method for a binocular vision system with an unknown imaging model is proposed. Based on the one-to-one mapping between 4-D image coordinates and 3-D Cartesian coordinates of spatial points, the intersection line of two calibration planes is extracted. All calibration planes are organized in the form of a three-plane group, and in each group, the poses are solved by the intersection lines. These poses are further optimized to acquire accurate 3-D coordinates of points in calibration planes. Combined with the correspondences of image pixels and points in a calibration plane, the line-plane intersection point between the projection line and this plane is calculated. Finally, projection lines are fitted based on corresponding line-plane intersection points. By modeling the relationship between image pixels and object-end projection lines, the uncertainty of the imaging model is solved. The proposed method is universal and stable for different imaging models including refraction, and the results of simulation and experiment show its effectiveness.