基于八叉树算法的多孔材料特征提取

通过对八叉树数据结构的分析,将闭孔材料的体数据转换成具有八叉树分层结点的体数据,详述了基于八叉树结点的孔泡逐层搜索算法的6步体积增长遍历和一步体积分解遍历步骤,给出了算法继续遍历的条件和终止遍历的3种可能,并从理论上证明了该遍历算法的完备性.在算法调用过程中,确定了孔泡基于体素为单位的体积和分布等参数的计算方法.利用仿真的柱状孔泡图像体数据,对八叉树遍历算法的提取效果进行了验证.实验结果表明,基于八叉树结构的遍历算法能准确提取闭孔材料中孔泡的体积和分布信息,为更有效地进行多孔材料性能分析奠定了基础.

Volumetric extraction of porous materials based on octree algorithm

Through the octree data structure analysis,a volumetric dataset of closed-cell porous materials is converted into a dataset of hierarchical octree nodes,and then the specific traversal search algorithm on the octree nodes is depicted in details,which is involved in six steps of the volume growth model and one step of the volume decomposition model.Moreover,the conditions of both the proceeding traversal and three possibilities of terminating are given,and the traversal algorithm of completeness is proved from a theoretical perspective.Finally,using a simulated volumetric dataset of columnar pores,the extracting effectiveness of the octree traversal algorithm is verified.The results show that the volume and the distribution information of pores can be successfully extracted by the proposed algorithm,which builds a solid foundation for a more effective performance analysis of porous materials.