An accurate stereo vision system using cross-shaped target self-calibration method based on photogrammetry

This paper presents an accurate stereo vision system for industrial inspection, which uses a self-calibration method based on photogrammetry. A cross-shaped calibration pattern which is portable and easy to be manufactured is designed. The cross target can be used to calibrate stereo vision systems and obtain higher measurement precision conveniently. The mathematical model of the stereo vision system with 10 distortion parameters for each camera is proposed. The feature point detection method with sub-pixel accuracy is explored. The calibration initial values are computed using the relative orientation method and the direct linear transform (DLT) method of photogrammetry. The bundle adjustment algorithm is used to optimize the calibration parameters as well as the 3D coordinates of the feature points. Experiment results show that the RMS error of the reprojection in our method is less than 0.05 pixels and the distance measurement error is 0.031 mm with a high precision scale bar which length is 221.001±0.003 mm.