Exploiting Self-Similarity in Geometry for Voxel Based Solid Modeling

Abstract

Voxel-based modeling techniques are known for their robustness and flexibility. However, they have three major shortcomings: (1) Memory intensive, since a large number of voxels are needed to represent high-resolution models (2) Computationally expensive, since a large number of voxels need to be visited (3) Computationally expensive isosurface extraction is needed to visualize the results. We describe techniques which alleviate these by taking advantage of self-similarity in the data making voxel-techniques practical and attractive. We describe algorithms for MEMS process emulation, isosurface extraction and visualization which utilize these techniques.