Laser imaging and approximation networks for calibration of three-dimensional vision

Abstract

An automatic calibration technique for three-dimensional vision is presented. This technique determines the vision parameters by means of approximation networks and image processing of a laser line. Also, the network performs the three-dimensional vision based on laser scanning and a mobile camera. The network is built based on the behavior of a laser line and the camera position. Here, an electromechanical device moves the camera during the vision task and the network provides an automatic re-calibration. Thus, the vision is carried out via mobile camera and extrinsic parameters are not passed to the system. Therefore, the accuracy and the performance of the vision procedure are improved. It is because the physical measurements of references are avoided. Thus, a contribution for the calibration of lighting methods is achieved. Additionally to it, the mobile setup provides a high sensitivity and avoids occlusion. The proposed technique is tested with real objects and its results are evaluated based on laser projection methods. To carry it out, a root mean square of error is computed using a contact method as reference. Also, the time processing is described.