Abstract
A technique for shape detection based on binocular imaging of a laser stripe is presented. In this technique, the object shape is recovered by means of laser stripe projection and binocular imaging. The approach of the binocular imaging in this technique is to avoid stripe occlusions, which appear due to the variation to the object surface. Based on the behavior of the stripe displacement, the object topography is computed by a Bezier approximation network. By means of this network, the measurements of the binocular geometry are avoided. The parameters of the binocular imaging are computed based on the Bezier approximation network. To reconstruct the topography, the object is scanned by a laser stripe. From the scanning, a set of binocular images of the stripe are processed to compute the object dimensions by means of the network. By applying Bezier approximation networks, the performance of the binocular imaging and the accuracy are improved. It is because the errors of the measurement are not added to the computational procedure, which performs the shape reconstruction. This procedure represents a contribution for the stripe projection methods and the binocular imaging. To describe the accuracy a root mean square of error is calculated. This technique is tested with real objects and its experimental results are presented. Also, the time processing is described. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 62–74, 2007