Feature-Preserving Hexahedral Mesh Generation from Industrial CT Image
Zichao Li, Yu‐Sheng Chen, Shanghu Shi, Liming Duan · 2024
Hexahedral mesh generation based on industrial Computed Tomography (CT) image is an important method in reverse design. However, maintaining the geometric corner features while ensuring mesh quality remains a challenge. To address this issue, this paper proposes a feature-preserving hexahedral mesh generation method based on three dimensional (3D) pixel feature recognition. First, the input CT images are recursively partitioned using an octree method to generate an internal mesh. Subsequently, corner points are extracted using pixel feature values obtained from the Shi-Tomasi algorithm, resulting in a feature map. The feature map is then transferred to the internal mesh, ensuring that the corner features are preserved. Finally, the boundary mesh is filled and optimized to ensure that they possess a positive scaled Jacobian, maintaining the mesh's regularity. Experimental results show that the proposed method effectively preserves sharp features while generating high quality hexahedral meshes.