Laser & Optoelectronics Progress, Volume. 59, Issue 14, 1415026(2022)
Three-Dimensional Pavement Texture Information Acquisition Based on Binocular Vision Algorithm
Figures & Tables(12)
Fig. 6. Sample and experimental site. (a) Sample diagram; (b) binocular measurement; (c) laser measurement
Fig. 7. Disparity maps obtained by different cost calculation methods. (a) Census; (b) Census+color information; (c) color information+gradient information
Fig. 8. Disparity maps obtained by different cost aggregation methods. (a) Guided filtering; (b) segmentation tree; (c) box filtering
Fig. 9. Parallax graphs obtained by the different algorithms. (a) SGBM; (b) algorithm before introducing cross scale aggregation model; (c) proposed algorithm
Fig. 10. Three dimensional model of laser measurement and the proposed algorithm measurement. (a) Laser measurement; (b) proposed algorithm measurement
Table 1. Detailed equipment parameters of the binocular vision measurement platform
View tableTable 1. Detailed equipment parameters of the binocular vision measurement platform
Equipment Parameter Content Camera Camera model MV-VDM200SM/SC Imaging resolution /（pixel×pixel） 1600×1200 Pixel size /（μm×μm） 4.4×4.4 Sensor type CCD Frame rate /（frame·s-1） 20 Exposure method Frame exposure Power /W 1.25
Table 2. MTD of asphalt pavement samples
View tableTable 2. MTD of asphalt pavement samples
Sample Measurement method MTD /mm Relative error /% 1 3D laser scanner 0.6788 3.15 Proposed algorithm 0.6574 2 3D laser scanner 1.203 2.99 Proposed algorithm 1.167
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Rong Jiang, Pan Zhu, Xinglin Zhou, Lu Liu. Three-Dimensional Pavement Texture Information Acquisition Based on Binocular Vision Algorithm[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415026
Paper Information
Category: Machine Vision
Received: Jul. 30, 2021
Accepted: Oct. 13, 2021
Published Online: Jul. 1, 2022
The Author Email: Pan Zhu (zhuyangpp@163.com)
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