可保留特徵與拓僕資訊並支援多重解析度之及時三維等位面擷取技術

Abstract

This dissertation presents a new method for surface extraction from volume data which generates surface adaptively without crack patch- ing, maintains consistent topology, preserves sharp features, and pre- serves the property of inter-cell independency. The presented ap- proach is based on the marching cubes algorithm, a popular method to convert volumetric data to polygonal meshes. The original march- ing cubes algorithm suffers from problems of cracks in adaptive reso- lution, inability to preserve sharp features, and topological inconsis- tency. Most of marching cubes variants only focus on one or some of these problems. Although these techniques could be combined to solve these problems altogether, such a combination might not be straightforward. Moreover, some feature-preserving variants intro- duce an additional problem, inter-cell dependency. The presented method provides a relatively simple and easy-to-implement solution to all these problems by converting 3D marching cubes into 2D cubical marching squares, resolving topology ambiguity with sharp features and eliminating inter-cell dependency by sampling additional sharp features on faces. Comparisons of our algorithm with other marching cubes variants demonstrate the effectiveness of presented method on various applications.