Improvement of Mesh Simplification Using Normal Vector Diversity

3D mesh simplification is an important challenge in various fields. While different simplification methods have been proposed in recent years, the focus has shifted to keeping properties such as ridges and valleys along with mesh simplification. While most of the proposed models have used curvature, some challenges exist, such as the computational complexity and sensitivity to the neighborhood size. The latter can be solved by averaging several neighborhoods. This paper proposes a simple yet fast method with less sensitivity to the neighborhood size. To this end, we use the normal vector and the parameters of a probability distribution of its variations to detect the elevations, depressions (geometrical changes), and curve parts. We combine this method with the Quadric Error Metric (QEM) method to produce a hybrid method for 3D mesh simplification, preserving its elevations and depressions. Evaluation results show that our method has a lower error than the other methods.