Iterative mapping for high-precision calibration and displacement measurements

The precision of calibration severely affects the precision of subsequent measurements. In the calibration, the corresponding image and global target coordinates are two distinct input datasets. The image coordinates may be estimated precisely with the use of an optimal feature detection algorithm. However, the global coordinates are usually chosen as the given 3D manufacturing centers, and are different from the reconstructed three-dimensional (3D) optical centers. In this study, an iterative coordinate mapping (ICM) method is proposed to optimize the 3D optical centers for high-precision calibration and displacement measurements. Precise optical 3D coordinates for a stereo-vision system calibration scheme are generated based on the results of the left and right camera calibrations. Herein, the principles of single-camera calibration, ICM method, precise coordinate generation, and stereo-vision system calibration schemes are presented. Computer simulations were performed to verify the effectiveness of the correction of 3D coordinates. Experiments were conducted to analyze the stability of the calibrated parameters and the precision of the reconstructed 3D coordinates. The results show that the ICM is with higher precision.