This paper presents a novel implicit representation of solid models. With this representation, every solid model can be effectively presented by three layered depth-normal images (LDNIs) that are perpendicular to three orthogonal axes respectively. The layered depth-normal images for a solid model, whose boundary is presented by a polygonal mesh, can be generated efficiently with help of the graphics hardware accelerated sampling. Based on this implicit representation - LDNIs, solid modeling operations including the Boolean operations and the offsetting operation have been developed. A contouring algorithm is also introduced in this paper to generate thin structure and sharp feature preserved mesh surfaces from the layered depth-normal images. Comparisons between LDNIs and other implicit representation of solid models are given at the end of the paper to demonstrate the advantages of LDNIs.
@article{arxiv.1009.0794,
title = {Layered Depth-Normal Images: a Sparse Implicit Representation of Solid Models},
author = {Charlie C. L. Wang and Yong Chen},
journal= {arXiv preprint arXiv:1009.0794},
year = {2010}
}