A Hybrid Digitization Mehtod For Reverse Engineering

Abstract

Methods for acquiring shape data generally can be classified into contact and non-contact. It is preferable to combine the use of scanner and CMM for digitisation. In this thesis, a hybrid digitization method is developed. Firstly, a filtering algorithm is developed that is able to thin the merged data points by eliminating noise and spurious data points with a user controlled tolerance bound. Secondly, we applied a region growing based triangulation algorithm to this set of thinned cloud data to form a triangular meshed surface model, with explicit feature information (boundaries & holes). Finally, we developed an algorithm to generate the probe paths for a CMM to recapture the key features of the object based on the information obtained from the triangulation process. Algorithms for the developed methods have been implemented using C/C++ on the OpenGL platform. Simulation results and actual case studies demonstrate the efficacy of the algorithms.