Fast and Accurate Plane Segmentation of Airborne LiDAR Point Cloud Using Cross-Line Elements
AbstractPlane segmentation is an important step in feature extraction and 3D modeling from light detection and ranging (LiDAR) point cloud. The accuracy and speed of plane segmentation are two issues difficult to balance, particularly when dealing with a massive point cloud with millions of points. A fast and easy-to-implement algorithm of plane segmentation based on cross-line element growth (CLEG) is proposed in this study. The point cloud is converted into grid data. The points are segmented into line segments with the Douglas-Peucker algorithm. Each point is then assigned to a cross-line element (CLE) obtained by segmenting the points in the cross-directions. A CLE determines one plane, and this is the rationale of the algorithm. CLE growth and point growth are combined after selecting the seed CLE to obtain the segmented facets. The CLEG algorithm is validated by comparing it with popular methods, such as RANSAC, 3D Hough transformation, principal component analysis (PCA), iterative PCA, and a state-of-the-art global optimization-based algorithm. Experiments indicate that the CLEG algorithm runs much faster than the other algorithms. The method can produce accurate segmentation at a speed of 6 s per 3 million points. The proposed method also exhibits good accuracy. View Full-Text
Share & Cite This Article
Wu, T.; Hu, X.; Ye, L. Fast and Accurate Plane Segmentation of Airborne LiDAR Point Cloud Using Cross-Line Elements. Remote Sens. 2016, 8, 383.
Wu T, Hu X, Ye L. Fast and Accurate Plane Segmentation of Airborne LiDAR Point Cloud Using Cross-Line Elements. Remote Sensing. 2016; 8(5):383.Chicago/Turabian Style
Wu, Teng; Hu, Xiangyun; Ye, Lizhi. 2016. "Fast and Accurate Plane Segmentation of Airborne LiDAR Point Cloud Using Cross-Line Elements." Remote Sens. 8, no. 5: 383.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.