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A low-cost approach for the estimation of rock joint roughness using photogrammetry.

Authors :
Ge, Yunfeng
Chen, Kaili
Liu, Geng
Zhang, Yongquan
Tang, Huiming
Source :
Engineering Geology. Aug2022, Vol. 305, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

To evaluate the possibility of utilizing commercially available devices for making joint roughness estimates, a digital single-lens reflex (DSLR) camera and a smartphone were used to reconstruct the three-dimensional models of 10 rock-joint specimens. The accuracy and efficiency were considered in investigating the performance of photogrammetry on the point clouds production and joint roughness estimation in the laboratory. Additionally, a handheld laser scanner was used in collecting high-resolution point clouds of the same specimens as reference data for evaluating the photogrammetry measurement accuracy. The interval for image capture was set at 8° with consideration for the data quality, point density, and computation time. The iterative closest point (ICP) algorithm was used to compare the surface topographies of the rock joints produced via photogrammetry and laser scanning. The point clouds generated by photogrammetry agreed with the laser-scanning results, with a small average difference (0.005 mm for the DSLR camera and 0.006 mm for the smartphone). Furthermore, two- and three-dimensional surface parameters were calculated using the three different sources of point clouds, which were in good agreement in the joint roughness estimates when comparing photogrammetry and laser scanning results. Comparative analyses revealed that both DSLR camera photogrammetry and smartphone photogrammetry can produce accurate point clouds of rock joints for roughness assessment; however, point clouds generated by the DSLR camera had higher accuracies than those generated by the smartphone. • The lens parameters determined in camera calibration differ from the nominal ones. • Interval between two camera positions affects the data accuracy and computation time. • Point clouds from photogrammetry are in good agreement with laser scanning data. • Similar estimates of joint roughness from photogrammetry and laser scanning data. • DSLR camera photogrammetry outperforms the smartphone for rock joint reconstruction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00137952
Volume :
305
Database :
Academic Search Index
Journal :
Engineering Geology
Publication Type :
Academic Journal
Accession number :
157352920
Full Text :
https://doi.org/10.1016/j.enggeo.2022.106726