基于点云的边界特征直接提取技术

RESEARCH ON DIRECT EXTRACTION OF BOUNDARY FROM POINT CLOUDS

边界作为反求工程CAD建模的重要几何特征信息,对重建曲面模型的品质和精度起着重要的作用。首先对点云数据进行空间三维划分,建立基于空间栅格的边界提取模型,然后通过研究线性时间复杂度的种子边界栅格识别和生长算法以及空间拓扑构型推理算法,实现从点云数据中直接获取边界信息。应用实例表明,算法的运行速度快、稳定性好,能够可靠地提取空间任意分布点云数据的内外边界。

As the most important geometry feature of CAD model in reverse engineering, how to accurately extract the boundary of point clouds is the key to guarantee the quality and precision of the final reconstructed surface. The mathematical model of boundary extraction is constructed firstly through the segmentation of the spatial box bounded by arbitrary uneven point clouds. Secondly, the seed recognition process and the seed growing process are implemented respectively to separate the boundary regions from the scattered point set by simple topology operation of 3-D grids. The feature points of boundary are extracted finally by applying topological-graph reasoning based on optimization of intrinsic geometry attribute. Empirical results show that the proposed algorithm is efficient and reliable in practice.