基于工业CT图像重构的网格模型的保特征简化方法

Simplification with feature preserving for mesh model reconstructed by industrial CT serial images

对基于工业CT图像重构的网格模型进行网格简化时,大多数现有网格模型简化算法会丢失特征,出现网格质量不好的问题。因此提出一种网格模型保特征简化方法,该方法用三角形折叠法对原始模型进行简化,当简化后模型的平均二面角角度误差达到允许误差后,再使用边折叠法对模型进行简化。在三角形折叠法中提出了利用被折叠三角形的法向量、各个顶点的高斯曲率及其在周边三角形上的投影确定该三角形的折叠点,利用局部体积误差与二面角角度误差的无因次化和确定折叠代价的方法;在边折叠法中提出了将二面角角度误差引入到二次误差测度(QEM)法的折叠代价中的改进QEM法。实验结果表明:与其他算法相比,该方法能够生成保特征、高质量、低几何误差的网格模型。

Most of the existing mesh simplification algorithms ignore some small features of the original model reconstructed by industrial CT serial images and the triangular meshes quality of the simplified model is poor.To solve this problem,a simplification method with feature preserving for mesh model was proposed.In this method,the original model was simplified by triangle collapse,and then after the average dihedral angle error of mesh model reached the allowable error,the model was simplified by edge collapse.For triangle collapse,the folding point of one triangle was determined by its normal vector,the Gaussian curvature of each vertex and vertices projection method.The collapsing cost of one triangle was determined by the sum of dimensionless number of its local volume error and its dihedral angle error.For edge collapse,the dihedral angle error was introduced in the edge collapse cost of QEM.The experiment result shows that the presented simplification method could generate the feature preserving,high quality and lower geometric error simplified model compared with most of the existing simplification algorithms.