| 利用原始激光雷达点云数据提取渐进式建筑物轮廓线 |
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| 引用本文： | 闻平,赵飞,吴小东,王莹,王冲.利用原始激光雷达点云数据提取渐进式建筑物轮廓线[J].测绘通报,2020,0(9):80-84. |
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| 作者姓名： | 闻平 赵飞 吴小东 王莹 王冲 |
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| 作者单位： | 1. 中国电建集团昆明勘测设计研究院有限公司, 云南 昆明 650051;2. 云南大学地球科学学院, 云南 昆明 650091 |
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| 基金项目： | 国家自然科学基金（41961064；41301520） |
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| 摘 要： | 建筑物是城市三维建模的重要元素，其轮廓信息的提取既是难点又是重点。本文提出了原始激光雷达点云数据的渐进式建筑物轮廓线提取方法。首先对原始点云数据采用渐进数学形态学滤波分离非地面点；然后使用改进的三维Hough转换分类出建筑物点云；进一步提取建筑物轮廓点，并根据相邻点方位角阈值确定建筑点云轮廓的关键点，以此简化并拟合建筑物轮廓线；最后基于轮廓线长度加权方向将建筑物轮廓规则化。结果表明，该方法大大提高了点云处理的效率和精度，可以直接从采集到的初始数据中自动化渐进式得到建筑物轮廓线信息。同时该方法对解决中小城镇建筑物体积小，距离近和屋顶坡度较大等问题具有较好的效果。
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| 关 键 词： | 建筑物轮廓线 原始LiDAR点云 三维Hough转换 轮廓线简化 长度加权规则化 |
| 收稿时间： | 2019-11-26 |
| 修稿时间： | 2020-01-12 |
Progressive building boundary extraction from original LiDAR point cloud data |
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| WEN Ping,ZHAO Fei,WU Xiaodong,WANG Ying,WANG Chong.Progressive building boundary extraction from original LiDAR point cloud data[J].Bulletin of Surveying and Mapping,2020,0(9):80-84. |
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| Authors: | WEN Ping ZHAO Fei WU Xiaodong WANG Ying WANG Chong |
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| Institution: | 1. Kunming Survey, Design and Research Institute Co., Ltd., of China Power Construction Group, Kunming 650051, China;2. School of Geosciences, Yunnan University, Kunming 650091, China |
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| Abstract: | Building is an important element of urban 3D modeling, and the extraction of building boundary information is both difficult and important. In this paper, a method is proposed to extract the regular building boundary from the original LiDAR point cloud data: Firstly, it uses the progressive mathematical morphology filter to separate the non ground points from the original point cloud data. Then it uses the improved 3D Hough transformation to classify the non ground points. On this basis, the key points are determined to simplify and fit the building boundary according to the azimuth threshold of the adjacent points. Finally, the building boundary is regularized based on the length weighted direction of the boundary. The results show that this method greatly improves the efficiency and accuracy of point cloud processing, and can automatically and incrementally obtain building boundary information directly from the initial data. At the same time, this method has a good effect on solving the problems of small building volume, close distance and large roof slope in small and medium-sized towns. |
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| Keywords: | building boundary original LiDAR point cloud 3D Hough transformation boundary simplification length weighted regularization |
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