Calibration modeling for mobile vision based laser imaging and approximation networks

A mobile calibration technique for three-dimensional vision is presented. In this technique, the parameters of mobile vision are computed automatically by approximation networks and image processing of a laser line. Also, the three-dimensional vision is performed by the networks. The proposed vision system provides online geometric modifications from the initial configuration. Here, an online re-calibration is performed via network data to determine the setup modifications. Thus, vision limitations caused by the geometric modifications are overcome. The network is built based on the behavior of the laser line and the camera position. In this manner, the network provides the data for the automatic re-calibration. This system avoids calibrated references and external procedures for re-calibration. Therefore, the calibration model improves the accuracy and performance of the mobile vision. It is because the external data are not passed to the procedure of the three-dimensional vision. This kind of modeling represents a contribution for calibration of mobile vision. To elucidate this contribution an evaluation is carried out based on the calibration via perspective projection model. The time processing is also described.