The Study of 3D Unorganized Data Points Reduction for Reverse Engineering

• Main Authors: Wen-tsung Wang, 王文聰
• Other Authors: Jung-hung Sun
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/42906252419467604460

碩士 === 國立高雄第一科技大學 === 機械與自動化工程所 === 93 === Reverse engineering offers a new process that objects can be digitized, reconstructed, and represented as computerized model fast and is an appropriate method for designing product with complex freeform surfaces. It is a powerful tool about the new product development in modern industry. Building such computerized model is a problem of growing importance since efficient 3D scanning technologies become more and more available. In order to sample 3D objects adequately, multiple scans have to be taken. Merging the measured points of each scan results is a large amount of unorganized data points. It creates the burden of large data points which must be manipulated, therefore, significantly require a large storage space and increase computational time. Data points reduction has become an important issue in Reverse engineering. But incorrectly reducing the point data will remove important information and lower the accuracy of CAD model. The aim of this research is to develop a data points reduction method for having complex freeform surface objects. Our approach is based on the theory of statistics and computational geometry, i.e. using the Principle Component Analysis(PCA) to analyze data point geometric information and to find the data point normal replaced by data point best fitting plane normal in small neighborhood, using the Region Growing(RG) Method to modify data point normal which on the rough region, using Spatial Divided(SD) Method to generate the 3D grids structure and subdivided grids by Octree Subdivided Algorithm to extract optimal data points. All algorithms of this research was developed and written in C++ and OpenGL. The proposed method was applied to test sample and the result will be compared with other points sampling methods from Surfacer 9.0 .