NDLI: 3D crack skeleton extraction from mobile LiDAR point clouds

Content Provider	IEEE Xplore Digital Library
Author	Yongtao Yu Li, J. Haiyan Guan Cheng Wang
Copyright Year	2014
Description	Author affiliation: Dept. of Geogr. & Environ. Manage., Univ. of Waterloo, Waterloo, ON, Canada (Haiyan Guan) \|\| Sch. of Inf. Sci. & Eng., Xiamen Univ., Xiamen, China (Yongtao Yu; Li, J.; Cheng Wang)
Abstract	This paper presents a novel algorithm for extracting 3D crack skeletons from 3D point clouds acquired by a mobile Light Detection and Ranging (LiDAR) system. This algorithm uses intensity information of cloud clouds to identify pavement cracks that usually exhibit lower intensities compared to their surroundings. First, crack candidates are extracted by applying the Otsu thresholding algorithm. Then, a spatial density filter is used to remove outliers. Next, crack points are grouped into crack-lines using a Euclidean distance clustering method. Finally, crack skeletons are extracted based on an L1-medial skeleton extraction method. The proposed algorithm has been tested on a set of mobile LiDAR point clouds acquired by a state-of-the-art RIEGL VMX-450 mobile LiDAR system. The results demonstrate the efficiency and reliability of the proposed algorithm in extracting 3D crack skeletons.
Sponsorship	IEEE Geosci. Remote Sens. Soc.
Starting Page	914
Ending Page	917
File Size	765250
Page Count	4
File Format	PDF
ISBN	9781479957750
DOI	10.1109/IGARSS.2014.6946574
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-13
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Skeleton Laser radar Roads Surface cracks Mobile communication Clustering algorithms L1-median Crack skeleton mobile LiDAR point cloud spatial density
Content Type	Text
Resource Type	Article

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