Assessment of the mined rock mass jointing based on aerial photography and computer vision methods

DOI: https://doi.org/10.30686/1609-9192-2023-5S-53-57

Читать на русскоя языкеV.P. Potapov, S.E. Popov
Federal Research Center for Information and Computational Technologies, Kemerovo Branch, Kemerovo, Russian Federation
Russian Mining Industry №5S / 2023 р. 53-57

Abstract: The task to assess rock mass jointing are currently usually solved in manual mode, which requires high qualification of the specialists and considerable time expenditures. Automation of such tasks is important in terms of reducing the time of image processing and obtaining additional information on the geomechanical state of the rock mass. The article discusses the possibilities of using computer vision and artificial intelligence technologies to assess jointing of the rock mass. For this purpose, aerial photography data obtained using unmanned aerial vehicles are used. The images are processed with the software developed by the authors, which performs tracing of the joints based on a neural network of a dedicated architecture. The results of processing aerial photography data are presented using the cases of coal strip mines in Kuzbass and open-pit mines of the Kola Peninsula. The use of neural network in processing of the aerial survey data of the rock masses has shown the promising potential of the method. After processing the data of tracing the jointing fields, it becomes possible to monitor the behavior of the rock mass by using the visualization tools for additional fields of characteristics, which allow to assess the nature of changes occurring under anthropogenic loads. The developed algorithms make it possible to significantly accelerate the processes of aerial survey data processing to assess the structural disturbance of the rock mass.

Keywords: aerial photography, rock mass, computer vision, neural networks, ELT technologies, information streams, containerization

Acknowledgments: The research was supported by the Russian Science Foundation Grant No.23-17-00148, https://rscf.ru/project/23-17-00148. The authors express their gratitude to the staff of the Mining Institute of the Kola Scientific Centre of the Russian Academy of Sciences, Apatity, Russia, Kozyrev A.A. and Lukichev S.V. for the materials provided and discussion of the paper

For citation: Potapov V.P., Popov S.E. Assessment of the mined rock mass jointing based on aerial photography and computer vision methods. Russian Mining Industry. 2023;(5S):53–57. https://doi.org/10.30686/1609-9192-2023-5S-53-57

Article info

Received: 27.10.2023

Revised: 22.11.2023

Accepted: 30.11.2023

Information about the authors

Vadim P. Potapov – Dr. Sci. (Eng.), Professor, Chief Research Associate, Federal Research Center for Information and Computational Technologies, Kemerovo Branch, Kemerovo, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Semen E. Popov – Cand. Sci. (Eng.), Senior Researcher, Federal Research Center for Information and Computational Technologies, Kemerovo Branch, Kemerovo, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

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