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Open AccessArticle

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

College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China
Upper Changjiang River Bureau of Hydrological and Water Resources Survey, Chongqing 400020, China
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(10), 608;
Received: 16 September 2020 / Revised: 10 October 2020 / Accepted: 18 October 2020 / Published: 20 October 2020
(This article belongs to the Special Issue Measuring, Mapping, Modeling, and Visualization of Cities)
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. View Full-Text
Keywords: mobile LiDAR; pseudo-scan line; filtering; edge detection; road marking mobile LiDAR; pseudo-scan line; filtering; edge detection; road marking
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MDPI and ACS Style

Yang, R.; Li, Q.; Tan, J.; Li, S.; Chen, X. Accurate Road Marking Detection from Noisy Point Clouds Acquired by Low-Cost Mobile LiDAR Systems. ISPRS Int. J. Geo-Inf. 2020, 9, 608.

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