Simplification and optimization of triangle meshing models reconstructed from slicing data

To solve the problem of huge amount of data sets and narrow triangles existed in triangular mesh model, a feature-preserving and high quality triangular mesh simplification and optimization method was studied. The method was divided into two stages: mesh simplification and mesh optimization. Firstly, it adopted quadric error metric based surface variation to compute the edge collapsing cost, and iteratively simplified mesh model according to the cost, which could efficiently preserve the features on the surface. Secondly, the local narrow triangles were optimized by a weighted second-order umbrella operator, and the quality of mesh model was improved by this way. The experiment results show that this method works well for preserving detailed information of feature regions whilst reliably producing high-quality and low geometrical error simplified mesh.