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| 海量点云数据轮廓特征线的快速生成算法 | |
| 引用本文： | 程效军,贾东峰,刘燕萍.海量点云数据轮廓特征线的快速生成算法[J].同济大学学报(自然科学版),2012,40(10):1559-1563. |
| 作者姓名： | 程效军 贾东峰 刘燕萍 |
| 作者单位： | 1. 同济大学测量与国土信息工程系,上海200092;同济大学现代工程测量国家测绘地理信息局重点实验室,上海200092 2. 同济大学测量与国土信息工程系,上海,200092 3. 同济大学浙江学院土木工程系,浙江嘉兴,314000 |
| 基金项目： | 基金项目：国家自然科学基金资助项目（40971241） |
| 摘 要： | 从海量点云数据中快速生成轮廓特征线,是实现基于特征的模型重建的关键.提出了一种基于切片的轮廓特征线快速生成算法.该算法首先对点云数据进行切片,将数字图像的方法应用到基于切片的特征点提取中,通过设置数字栅格平面的边长快速地提取特征点,并根据提出的双向索引连通法快速构造特征线,最终实现了点云数据的曲线模型.实例证明:本算法可以快速、准确地生成海量点云数据的轮廓特征线. |
| 关 键 词： | 海量点云 轮廓特征线 切片 数字图像 曲线模型 |
| 收稿时间： | 8/23/2011 3:19:16 PM |
| 修稿时间： | 2012/6/12 0:00:00 |
A Fast Contour Generation Algorithm of Massive Point Cloud Data |
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| CHENG Xiaojun,JIA Dongfeng and LIU Yanping.A Fast Contour Generation Algorithm of Massive Point Cloud Data[J].Journal of Tongji University(Natural Science),2012,40(10):1559-1563. | |
| Authors: | CHENG Xiaojun JIA Dongfeng and LIU Yanping |
| Institution: | Department of Survey and Geo informatics, Tongji University, Shanghai 200092, China; Key Laboratory of Advanced Engineering Surveying of National Administration of Surveying, Mapping and Geoinformation, Shanghai 200092, China;Department of Survey and Geo informatics, Tongji University, Shanghai 200092, China;Department of Civil Engineering, Tongji University Zhejiang College, Jiaxing 314000, China |
| Abstract: | Rapid generation of contour from massive point cloud data is the crucial step for feature based model reconstruction. This paper proposes a fast contour generation algorithm of massive point cloud data based on slicing. To extract the featured points (FPs) from slice, a layer based point cloud model is directly generated from the point cloud data and serves as the input of a digital image based method. Meanwhile, the size of the grid of digital plane is discussed for fast getting FPs. Based on the FPs of each slice, bidirectional index connecting method (BICM) is put forward to quickly construct layer contour. Finally, the curve model is generated. Several case studies are presented to illustrate the efficiency and accuracy of this approach. |
| Keywords: | massive point cloud contour slice digital image curve model |
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