Rough surface modeling using surface growth

In this paper, we present a novel modeling method for synthesizing rough surfaces using discrete surface growth models. We employ a two-pass method. Initial point cluster data is generated using discrete simulation models derived from physical surface growth and evolution. Then, a final surface is reconstructed from the point clusters by a level set method. Since many rough surfaces in nature are formed by deposition and diffusion processes, discrete models simulating these processes can reasonably reproduce natural rough surfaces. These discrete models are easy to implement and efficient enough for interactive control. After generating initial data set from the application of a discrete model, a level set method is used to obtain implicit surface representations. This approach allows us to easily handle complex surface topologies. We demonstrate that our approach allows a flexible and general way to create various rough surfaces.