方向感知的网格模型特征识别

针对网格模型平滑区域提取特征困难，以及现有特征识别方法无法检测仅沿某一特定方向分布的特征点的问题，提出一种方向感知的网格模型特征识别方法。首先，分别从x、y、z三个方向探测网格顶点邻接面法向量沿不同方向变化的情况。设定合适的阈值，只要检测到在任何一个方向上顶点邻接面法向量的变化超过阈值，该顶点即被识别为特征点。然后，针对现有网格模型特征识别算法无法检测三维医学模型普遍存在的一种仅沿z轴方向分布的梯田型结构的问题，单独探测医学模型网格顶点邻接面法向量沿z轴方向变化的情况，将变化超出阈值的顶点识别为梯田型结构顶点，正确地将非正常梯田型结构从人体模型正常结构特征中分离出来。与二面角法的对比实验的结果显示：在相同阈值设置下，所提方法能更好地识别出网格模型特征，解决了二面角法在没有明显折线的平滑区域上无法有效识别特征点的问题；同时，也解决了现有网格模型特征检测算法因不具备方向探测能力而无法将医学模型非正常梯田型结构与正常人体结构区分开来的问题，为医学模型后续数字几何处理工作提供了条件。

Direction-perception feature recognition on mesh model

In order to solve the problems of the difficulty to extract features on the smooth regions of mesh models and the impossibility to recognize the feature vertices distributed only along one specific direction by the existing feature detection methods, a direction-perception method of feature recognition on mesh models was proposed. Firstly, the changes of the normal vectors of the mesh vertex adjacent surfaces were detected in x, y and z directions separately. With a suitable threshold set, if the change of a normal vector of the mesh vertex adjacent surfaces exceeded the threshold in any direction, the vertex would be recognized as a feature vertex. Then, concerning the problem that the existing mesh model feature detection algorithms cannot recognize the terraced field structure only distributed along the z-axis of three-dimensional medical model, the algorithm detected the change of normal vectors of the mesh vertex adjacent surfaces just along the z-axis direction, and recognized the vertex as a terraced field structure vertex once the change of the vertex exceeds the threshold. The abnormal terraced field structures were separated from the normal structures of the human body successfully. The experimental results show that, compared with the dihedral angle method, the proposed method can identify the features of the mesh model better under the same conditions. The proposed method solves the problem that the dihedral angle method cannot effectively identify the feature vertices on the smooth regions without obvious broken lines, and also solves the problem that the existing mesh model feature detection algorithms cannot distinguish the abnormal terraced field structures from the normal human body structures due to the lack of the direction detection ability, and establishes a base for the following digital geometry processing of the medical model.