Study On The Key Techniques For 3D Scanner And Reverse Engineering

Along with the development of computer technology, an urgent request, that is how to obtain 3D model of objects, is put forward in industrial production, movie making, apparel design, medical diagnosis and military training etc. 3D scanner is a kind of input equipment which can acquire the 3D data of an object directly. This technology comes to be known as Reverse Engineering. 3D scanner realtes to such subjects as optics, mechanics, electronics, automatic control, image process etc and has much significance on many applications. In this dissertation, some key technology used in 3D scanner are developed including 3D acquiring, system calibration, data repairing, point cloud compression, 3D reconstruction and triangle mesh simplification. My work has been supported by National Natural Science Fundation (69775022) and National 863 Project (863-306-ZT04-06-3). First, to the fields of 3D acquiring, it systematically concludes the popular 3D acquiring methods and some products of 3D scanner. The basic process and key technology are also presented. 3D scanner can be divided into two types according to its acquiring method: contact and non-contact. The former uses probe to touch the surface of objects and obtain the coordination from geometry structure. The latter gets 3D information from a series of photographs of video camera based on computer vision theory. Considering different applications, we developped contact multi-joint 3D scanner(3dlcs-400) and non-contact constructed lighting 3D scanner(3dlcs-200). The theory, constitute and work process are introduced. System parameter errors will result in the coordination errors. In order to improve measuring accuracy, it is necessary to calibrate the structure parameters. Combined with fast convergence and high accuracy, a hybrid intelligent algorithm is proprosed to solve the parameter calibration of the nonlinear system. The results that computed through the improved least-square algorithm become the the original values of the genetic algorithm where gene range could be dynamically changed. The experiment shows that the hybrid algorithm is valid in practical application. Because of some restrictions, incomplete data is possible to appear in the scanning process. Data repairing based on genetic algorithm and BP neural network is investigated to solve the problem. With the improvement of accuracy, the number of point cloud increases quickly and needs to be compressed. The simplest method uses sampling at the cost of quality, so it is not fit for complex object's surface. In this dissertation, an adaptive 3D Splitting method for compressing of the data on the spacial contours is presented. Triangle mesh model is selected to build boundary representation. The reconstruction methods with orderliness data and scattered data are discussed. The new way uses a set of multilayer parallel planes to bed the set of scattered points. First, we regulate the scattered points into a serial of contour lines. Seconed, we sort the points in the same of contour lines in anticlockwise. Final, we reconstruct the object with the way of parallel contour lines. Nowadays, the quantity of triangle mesh becomes more and more to meet the demand of reality sensation. But complex mesh model is adverse to storage, transfer and render. Progressive mesh is a good method to simplify meshes. In PM form, an arbitrary mesh is stored as a much coarser mesh together with a sequence of detail records that indicate how to incrementally refine exactly back into the original mesh. The PM representation naturally supports progressive transmission, offers a concise encoding of itself, and permits selective refinement. On the basis of PM, a new method which collaspe half edge and keep the color attributes is given. It not only avoids the complexity of computing new vertex, but also embodys the effect of color. The practical results appear perfect.