A Complementary Topographic Feature Detection Algorithm Based on Surface Curvature for Three-Dimensional Level-Set Functions

Abstract The level-set method is widely used in expanding front simulations numerous fields of computational research, such as computer graphics, physics, or microelectronics. In the latter, employed for topography semiconductor device fabrication processes, being driven by complicated physical and chemical models. These models tend to produce surfaces with critical points where accuracy paramount. To efficiently increase regions neighboring these points, automatic hierarchical domain refinement required, guided robust feature detection. Feature detection has be computationally efficient sufficiently accurate reliably detect points. that end, we present a fast parallel geometric algorithm three-dimensional functions. Our approach based on two different, complementary curvature calculation methods zero an optimized parameter features. For performance reasons, our can principal linked different methods, however, will discussed, particularly attractive options are available: (i) A novel extension standard functions, (ii) often disregarded calculating due its purported low numerical accuracy. We show, latter still viable option, able features geometries stemming from complicated, practically relevant geometries. findings applicable other applications surface simplification.