Automating laser scanning of 3-D surfaces for reverse engineering

Application of current 3-D laser scanning systems to reverse engineering is limited by two obstacles. The meticulous guidance of the laser scanner over the surface of the object being scanned and the segmentation of the cloud data which is collected by the laser scanner. Presently, both obstacles are being manually salved. The guidance of the laser scanning sensor at the correct surface to sensor distance is dependent on operator judgement and the segmentation of the collected data is reliant on the user to manually define surface boundaries on a computer screen. By applying a 2-D CCD camera, both of these problems can be resolved. Depth information on the location of the object surface can be derived from a pair of stereo images from the CCD camera. Using this depth information, the scanner path can be automatically calculated. Segmentation of the object surface can be accomplished by employing a Kohonen neural network onto the CCD image. Successful segmentation of the image is conditional on the locations selected to start neural nodes as well as the prevention of the neuron connectors from bleeding onto neighbouring patches. Thus the CCD camera allows for the automatic path planning of the laser scanner as well as the segmentation of the surface into patches defined along its natural boundaries.