3D Vision Measurement Method And Realization Technique Based on Radical Basis Function

摘要

A new vision location method based on radical basis function networks (RBFN) is presented in this paper. It fully utilizes the excellent ability of RBFN to approach the nonlinear mapping and have a good performance of high learning rale and adapting the different environment generalization. It sets up a non-linear relationship between the space sample points and the corresponding image information by learning, instead of traditional calibration method, and can be used for 3D measurement. In our lab. it was applied to 3D vision location system based on a multi-linear photoelectrical sensor system. The experiment proves that it can quickly realize high-accuracy space location. This method could be supplied as a new one to solve the 3D space location problem.