TY - JOUR
T1 - Field Imaging and Volumetric Reconstruction of Riprap Rock and Large-Sized Aggregates
T2 - Algorithms and Application
AU - Huang, Haohang
AU - Luo, Jiayi
AU - Moaveni, Maziar
AU - Tutumluer, Erol
AU - Hart, John M.
AU - Beshears, Sheila
AU - Stolba, Andrew J.
N1 - Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2019.
PY - 2019
Y1 - 2019
N2 - Riprap rock and large-sized aggregates have been used extensively in geotechnical and hydraulic engineering. They essentially provide erosion control, sediment control, and scour protection. The sustainable and reliable use of riprap materials demands efficient and accurate evaluation of their large particle sizes, shapes, and gradation information at both quarry production lines and construction sites. Traditional methods for assessing riprap geometric properties involve subjective visual inspection and time-consuming hand measurements. As such, achieving the comprehensive in-situ characterization of riprap materials still remains challenging for practitioners and engineers. This paper presents an innovative approach for characterizing the volumetric properties of riprap by establishing a field imaging system associated with newly developed color image segmentation and three-dimensional (3-D) reconstruction algorithms. The field imaging system described in this paper with its algorithms and field application examples is designed to be portable, deployable, and affordable for efficient image acquisition. The robustness and accuracy of the image segmentation and 3-D reconstruction algorithms are validated against ground truth measurements collected in stone quarry sites and compared with state-of-the-practice inspection methods. The imaging-based results show good agreement with the ground truth and provide improved volumetric estimation when compared with currently adopted inspection methods. Based on the findings of this study, the innovative imaging-based system is envisioned for full development to provide convenient, reliable, and sustainable solutions for the onsite Quality Assurance/Quality Control tasks relating to riprap rock and large-sized aggregates.
AB - Riprap rock and large-sized aggregates have been used extensively in geotechnical and hydraulic engineering. They essentially provide erosion control, sediment control, and scour protection. The sustainable and reliable use of riprap materials demands efficient and accurate evaluation of their large particle sizes, shapes, and gradation information at both quarry production lines and construction sites. Traditional methods for assessing riprap geometric properties involve subjective visual inspection and time-consuming hand measurements. As such, achieving the comprehensive in-situ characterization of riprap materials still remains challenging for practitioners and engineers. This paper presents an innovative approach for characterizing the volumetric properties of riprap by establishing a field imaging system associated with newly developed color image segmentation and three-dimensional (3-D) reconstruction algorithms. The field imaging system described in this paper with its algorithms and field application examples is designed to be portable, deployable, and affordable for efficient image acquisition. The robustness and accuracy of the image segmentation and 3-D reconstruction algorithms are validated against ground truth measurements collected in stone quarry sites and compared with state-of-the-practice inspection methods. The imaging-based results show good agreement with the ground truth and provide improved volumetric estimation when compared with currently adopted inspection methods. Based on the findings of this study, the innovative imaging-based system is envisioned for full development to provide convenient, reliable, and sustainable solutions for the onsite Quality Assurance/Quality Control tasks relating to riprap rock and large-sized aggregates.
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U2 - 10.1177/0361198119848704
DO - 10.1177/0361198119848704
M3 - Article
AN - SCOPUS:85065796944
SN - 0361-1981
VL - 2673
SP - 575
EP - 589
JO - Transportation Research Record
JF - Transportation Research Record
IS - 9
ER -