建筑轮廓线提取与规则化是LIDAR数据处理和建筑三维建模的重要步骤和技术难点.首次将"Alpha Shapes算法"应用于LIDAR数据处理,实践证明该算法简洁高效、运行稳定、提取精度高,适用于任何形状的建筑轮廓线提取,并具有一定自适应性和滤波功能,非常适合LIDAR点云数据提取建筑轮廓线.同时,提出了改进的"管子算法"用于原始轮廓线的简化,提出了适用于四边形的"矩形外接圆法"和适用于多边形(大于四边且边数为偶数)的"分类强制正交法"以进一步实现轮廓线的规则化,最终解决了离散点云提取规则建筑轮廓线的核心问题.实践证明,本文所述算法适用于凸凹多边形建筑内外轮廓线的提取与规则化.

The building boundary extraction and normalization are the key approach for LIDAR data processing and building 3Dmodeling. In thispaper,“Alpha Shapes algorithm”is firstapplied on the LIDAR data to extract the building boundary. In addition, an enhanced boundary smi plifying algorithm,.i e.“Pipe Algorithm”and two other developed normalization algorithms,“Circumcircle Regularization Algorithm”&“Cluster and AdjustmentAlgorithm”are used to mi prove the extracted boundary.Finally, the normalized building boundary is generated perfectlywith these algorithms.A lmi ited accumulated pointsS hasan alpha shape in polygon. Thispolygon isdetermined by Sandα.We can mi agine that a circlewith anαradius is rolling around theS. Whenαvalue is big enough, the circlewill not fall into the area of accumulated points.The rolling trackwill form the boundaryofthese discrete points(forexampleLIDAR data). Contrarily,when theαvalue is very small(α→0), every pointmightbe the boundary.When the alpha value is approaching infinity(α→∞), alpha shape will be the convex hul.l When theScontains evenly distributed points andαvalue approaching optmi um value,the alpha shape can extract the inner and outerboundary of convex and concave polygon.The boundary obtained from Alpha ShapeAlgorithm above is rough which can be defined as raw boundary. In this paper,an enhanced smi plifying algorithm,.i e.“PipeAlgorithm”isdeveloped to smi plify the raw outlinewhich usually is composed of zigzag shape.PipeAlgorithm retrieves the polygon inflexion points based on the changes of angle direction.These inflexion points are retained while the intermediate points are elmi inated. The remained inflexion points will establish a basic framework of the polygon.At the same tmi e,two otherdeveloped normalization algorithms, CircumcircleRegularizationAlgorithm&Clusterand AdjustmentAlgorithm are used to mi prove the extracted polygon framework. Now, the two normalization algorithms can be applied for four sided andmulti-sided polygon(greater than four sides and the number of sidemustbe even number).Comparedwith other algorithms,“Alpha Shapes”algorithm can effectively and stably process LIDAR points-cloud datawith high precision. At the same tmi e,it can keep fine features of any building shape boundary while filter the footprints ofnon-building. The expermi entresults show that these algorithms are excellent in buildingboundary (convex&concave polygons) extraction and normalization. The errorbetween the extracted building boundary and the actualoutline is usually less than 0.5 m.