scholarly journals Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds

Sensors ◽  
2016 ◽  
Vol 16 (6) ◽  
pp. 903 ◽  
Author(s):  
Li Yan ◽  
Hua Liu ◽  
Junxiang Tan ◽  
Zan Li ◽  
Hong Xie ◽  
...  
Keyword(s):  
Point Clouds ◽  
Scan Line ◽  
Road Marking

scholarly journals Accurate Road Marking Detection from Noisy Point Clouds Acquired by Low-Cost Mobile LiDAR Systems

2020 ◽  
Vol 9 (10) ◽  
pp. 608
Author(s):  
Ronghao Yang ◽  
Qitao Li ◽  
Junxiang Tan ◽  
Shaoda Li ◽  
Xinyu Chen
Keyword(s):  
Low Cost ◽  
Point Clouds ◽  
The Road ◽  
Online Processing ◽  
Beam Laser ◽  
Intensity Information ◽  
Laser Scanners ◽  
Quantitative Results ◽  
Scan Line ◽  
Road Marking

Road markings that provide instructions for unmanned driving are important elements in high-precision maps. In road information collection technology, multi-beam mobile LiDAR scanning (MLS) is currently adopted instead of traditional mono-beam LiDAR scanning because of the advantages of low cost and multiple fields of view for multi-beam laser scanners; however, the intensity information scanned by multi-beam systems is noisy and current methods designed for road marking detection from mono-beam point clouds are of low accuracy. This paper presents an accurate algorithm for detecting road markings from noisy point clouds, where most nonroad points are removed and the remaining points are organized into a set of consecutive pseudo-scan lines for parallel and/or online processing. The road surface is precisely extracted by a moving fitting window filter from each pseudo-scan line, and a marker edge detector combining an intensity gradient with an intensity statistics histogram is presented for road marking detection. Quantitative results indicate that the proposed method achieves average recall, precision, and Matthews correlation coefficient (MCC) levels of 90%, 95%, and 92%, respectively, showing excellent performance for road marking detection from multi-beam scanning point clouds.

scholarly journals An Approach for Segmentation of Airborne Laser Point Clouds Utilizing Scan-Line Characteristics

ETRI Journal ◽  
2007 ◽  
Vol 29 (5) ◽  
pp. 641-648 ◽  
Author(s):  
Soo-Hee Han ◽  
Jeong-Ho Lee ◽  
Ki-Yun Yu
Keyword(s):  
Point Clouds ◽  
Airborne Laser ◽  
Scan Line

scholarly journals Concrete Spalling Detection for Metro Tunnel from Point Cloud Based on Roughness Descriptor

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Hangbin Wu ◽  
Xingran Ao ◽  
Zhuo Chen ◽  
Chun Liu ◽  
Zeran Xu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Projected Area ◽  
Roughness Analysis ◽  
Bolt Holes ◽  
Scan Line ◽  
Metro Tunnel ◽  
Area Classification ◽  
Line Fitting

Automatic concrete spalling detection has become an important issue for metro tunnel examinations and maintenance. This paper focuses on concrete spalling detection research with surface roughness analysis based on point clouds produced by 3D mobile laser scanning (MLS) system. In the proposed method, at first, the points on ancillary facilities attached to tunnel surface are considered as outliers and removed via circular scan-line fitting and large residual error filtering. Then, a roughness descriptor for the metro tunnel surface is designed based on the triangulated grid derived from point clouds. The roughness descriptor is generally defined as the ratio of surface area to the projected area for a unit, which works well in identifying high rough areas on the tunnel surface, such as bolt holes, segment seams, and spalling patches. Finally, rough area classification based on Hough transformation and similarity analysis is performed on the identified areas to accurately label patches belonging to segment seams and bolt holes. After removing the patches of bolt holes and segment seams, the remaining patches are considered as belonging to concrete spalling. The experiment was conducted on a real tunnel interval in Shanghai. The result of concrete spalling detection revealed the validity and feasibility of the proposed method.

scholarly journals Fast Ground Filtering of Airborne LiDAR Data Based on Iterative Scan-Line Spline Interpolation

2019 ◽  
Vol 11 (19) ◽  
pp. 2256 ◽  
Author(s):  
Jorge Martínez Sánchez ◽  
Álvaro Váquez Álvarez ◽  
David López Vilariño ◽  
Francisco Fernández Rivera ◽  
José Carlos Cabaleiro Domínguez ◽  
...  
Keyword(s):  
Real Time ◽  
Spline Interpolation ◽  
Total Error ◽  
Hardware Acceleration ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Wide Range ◽  
Scan Line ◽  
Airborne Lidar Data

Over the last two decades, a wide range of applications have been developed from Light Detection and Ranging (LiDAR) point clouds. Most LiDAR-derived products require the distinction between ground and non-ground points. Because of this, ground filtering its being one of the most studied topics in the literature and robust methods are nowadays available. However, these methods have been designed to work with offline data and they are generally not well suited for real-time scenarios. Aiming to address this issue, this paper proposes an efficient method for ground filtering of airborne LiDAR data based on scan-line processing. In our proposal, an iterative 1-D spline interpolation is performed in each scan line sequentially. The final spline knots of a scan line are taken into account for the next scan line, so that valuable 2-D information is also considered without compromising computational efficiency. Points are labelled into ground and non-ground by analysing their residuals to the final spline. When tested against synthetic ground truth, the method yields a mean kappa value of 88.59% and a mean total error of 0.50%. Experiments with real data also show satisfactory results under visual inspection. Performance tests on a workstation show that the method can process up to 1 million points per second. The original implementation was ported into a low-cost development board to demonstrate its feasibility to run in embedded systems, where throughput was improved by using programmable logic hardware acceleration. Analysis shows that real-time filtering is possible in a high-end board prototype, as it can process the amount of points per second that current lightweight scanners acquire with low-energy consumption.

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