Fast Algorithms for the fatting of 3D Surfaces

• Main Authors: Kuo-Feng Kao, 高國峰
• Other Authors: Yih-Chuan Lin
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/27420475256177246152

碩士 === 樹德科技大學 === 資訊管理研究所 === 91 === The goal research in this paper is showing how to fast the algorithms for 3D surfaces flattening by deriving homologous 2D patterns from triangulated 3D surfaces. Many industries, such as shoemaking, clothing factory, shipbuilding industry, cartography, medical equipment industry and manufacturing industry etc., applied the important function of 3D Surfaces flattened into 2D patterns in CAD/CAM systems. To use this function can get the information about the flat surface automatically, and also provide the key data for the following designing and manufacturing process. But flattening 3D surfaces into 2D patterns has usually including complex 3D surfaces in the illustrated cases. For example, like elliptical curvature and hyperbolic curvature, these two kinds of non-developable surface require a considerable computing and time-consuming process. Besides it’s easily to result the inaccuracy problem when we are trying to flatten it. If we want to decrease the inaccuracy problem and raise the quality at the same time, it will take much more time to correct the error. Thus, methods of speeding up the unfolding process are the focus in this paper. In order to do this research, an extensive literature review on the current status of methods has conducted first. We paid more attention to improve a method that was proposed by McCartney in 1999.In his literature of surfaces flattening that the material’s thickness and elasticity is out of consideration. In his work, McCartney gave a more systematic solution description than others do the same thing, and the algorithm performs well in the illustrated cases. However, the algorithm of McCartney requires a considerable computing and a time-consuming process when the 3D surfaces become larger or more complex. So, in this research we presented new concepts about using the Max heap tree of data structure and the energy can be storing to do the improvement in 3D surfaces flattening.