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Proceedings Paper

A real-time 3D scanning system for pavement rutting and pothole detections
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Paper Abstract

Rutting and pothole are the common pavement distress problems that need to be timely inspected and repaired to ensure ride quality and safe traffic. This paper introduces a real-time, automated inspection system devoted for detecting these distress features using high-speed transverse scanning. The detection principle is based on the dynamic generation and characterization of 3D pavement profiles obtained from structured light measurements. The system implementation mainly involves three tasks: multi-view coplanar calibration, sub-pixel laser stripe location, and pavement distress recognition. The multi-view coplanar scheme was employed in the calibration procedure to increase the feature points and to make the points distributed across the field of view of the camera, which greatly improves the calibration precision. The laser stripe locating method was implemented in four steps: median filtering, coarse edge detection, fine edge adjusting, stripe curve mending and interpolation by cubic splines. The pavement distress recognition algorithms include line segment approximation of the profile, searching for the feature points, and parameters calculations. The parameter data of a curve segment between two feature points, such as width, depth and length, were used to differentiate rutting, pothole, and pothole under different constraints. The preliminary experiment results show that the system is capable of locating these pavement distresses, and meets the needs for real-time and accurate pavement inspection.

Paper Details

Date Published: 4 September 2009
PDF: 9 pages
Proc. SPIE 7447, Videometrics, Range Imaging, and Applications X, 74470B (4 September 2009); doi: 10.1117/12.824559
Show Author Affiliations
Qingguang Li, The Univ. of Texas at Austin (United States)
Ming Yao, The Univ. of Texas at Austin (United States)
Xun Yao, The Univ. of Texas at Austin (United States)
Wurong Yu, The Univ. of Texas at Austin (United States)
Bugao Xu, The Univ. of Texas at Austin (United States)


Published in SPIE Proceedings Vol. 7447:
Videometrics, Range Imaging, and Applications X
Fabio Remondino; Mark R. Shortis; Sabry F. El-Hakim, Editor(s)

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