Point cloud error compensation method for stereo structured light 3D reconstruction system

In order to improve the accuracy of stereo structured light 3D reconstruction system, a point cloud error compensation method is proposed. The method is divided into three parts: error calibration, error modeling and error compensation. Firstly, a new error calibration method is proposed, which divides the measurement space of stereo vision structured light system into discrete feature points, and calibrates the error of feature points in the whole space. Secondly, the error modeling method based on neural network is proposed, and the error model of this space is established. Finally, a point cloud error compensation method suitable for stereo vision structured light system is proposed. After experiments, it is proved that the proposed error compensation method reduces the diameter error by 51.96% and the sphere center distance error by 14.16%, respectively. The effectiveness and feasibility of this algorithm are also verified.