Automatic extraction and evaluation of pavement three-dimensional surface texture using laser scanning technology

Wang, Yuchen; Yu, Bin; Zhang, Xiaoyu; Jia, Liang

doi:10.1016/j.autcon.2022.104410

Cited by 23 publications

(6 citation statements)

References 28 publications

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“…We set the shutter time as 0.3ms and set the resolution as 0.4 mm to accelerate testing speed. Relevant research showed that the main action area of road wear was the macroscopic texture part of the road surface with a wavelength size of 0.5-50m [10] . Therefore, the settings were reasonable.…”

Section: Data Acquisitionmentioning

confidence: 99%

Intelligent detection of asphalt pavement abrasion status based on laser and mobile images

Chen,

Xie,

et al. 2023

International Conference on Precision Instruments and Optical Engineering (PIOE 2023)

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Section: Data Acquisitionmentioning

confidence: 99%

Intelligent detection of asphalt pavement abrasion status based on laser and mobile images

Chen,

Xie,

et al. 2023

International Conference on Precision Instruments and Optical Engineering (PIOE 2023)

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“…The fine laser on the road surface can reflect the condition of the ground as well as the distribution location of its surface objects. Extracting the laser lines from the image can get the contour texture about the ground and the morphology of its surface objects, and by combining the moving laser and the extraction of laser lines in multiple frames, we can get the comprehensive three-dimensional depth information of the road, which can more comprehensively describe the condition of the road and the characteristics of the surface objects [3] . Therefore, the extraction of laser streaks is a key factor in visual detection research.…”

Section: Introductionmentioning

confidence: 99%

Accurate laser line extraction algorithm based on morphological features under strong interference

Wu,

2024

MIPPR 2023: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications

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In outdoor complex lighting environments, laser stripe extraction becomes challenging due to the possibility of strong exposures in the external environment as well as reflective interference on the road surface. In order to overcome these problems, this paper proposes a multi-feature structured light extraction algorithm based on seed neighborhoods, which utilizes multiple seed points and comprehensively considers the laser stripe features, especially the morphological features of the optical stripes in their surrounding neighborhoods, so as to obtain the approximate distribution location of the real laser stripe. Finally, the laser streak extraction is performed by the gradient difference of the optical streak boundary as well as its own brightness. The experimental results show that the method is still effective in extracting laser lines even in high exposure environments where there are interferences such as reflections on the road surface.

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“…For example, the Steger algorithm uses the Hessian matrix to calculate the normal vector of the light stripe; however, it is computationally complex. 11 Qi et al and Wang et al improved the Steger algorithm; 12,13 however, their improvements are poor for the extraction of non-robust light stripes. The directional template method (DTM) was poor in robustness and accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…and Wang et al. improved the Steger algorithm; 12 , 13 however, their improvements are poor for the extraction of non-robust light stripes. The directional template method (DTM) was poor in robustness and accuracy 14 .…”

Section: Introductionmentioning

confidence: 99%

High-precision multi-curvature line-structured light center extraction algorithm based on a tooth model

Tang,

Jiang,

Miao

et al. 2023

Opt. Eng.

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Common line-structured light center extraction algorithms have limitations in accuracy and robustness when extracting the center of line-structured light obtained from objects with complex surface structures. In this study, we propose a high-precision center extraction algorithm for multi-curvature line-structured light. This algorithm improves the enhanced parallel thinning algorithm to eliminate redundant points and burrs and fills for missing center points at the end of the light stripe via the improved internal propulsion center extraction algorithm. Finally, sub-pixel centers are recalculated in the direction of the normal vector. A comparative experiment using three classical algorithms was conducted based on a tooth model with a complex curved surface. The experimental results show that the mean absolute error of this algorithm is <0.1, which is only half that of the best-performing dual-threshold grayscale center-of-gravity method in the classical method. Extraction of the center can be performed for multi-curvature line-structured light over 20 curvatures in the range of ð0.0001; 4.1439Þ∕pixel −1 ; moreover, the end of the light stripe and the identification of the truncation can be improved. Therefore, the proposed algorithm is suitable for contour detection of multi-curvature targets and effectively improves the accuracy of high-precision object detection.

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Automatic extraction and evaluation of pavement three-dimensional surface texture using laser scanning technology

Cited by 23 publications

References 28 publications

Intelligent detection of asphalt pavement abrasion status based on laser and mobile images

Intelligent detection of asphalt pavement abrasion status based on laser and mobile images

Accurate laser line extraction algorithm based on morphological features under strong interference

High-precision multi-curvature line-structured light center extraction algorithm based on a tooth model

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