Development of photogrammetric models based on video survey data of underground mine workings in low-light conditions

DOI: https://doi.org/10.30686/1609-9192-2025-6-187-193

Читать на русскоя языке Fedotenko V.S.1, Kirkov A.E.1, Radchenko D.N.1, Averin A.P.1
1  Institute of Comprehensive Exploitation of Mineral Resources of the Russian Academy of Sciences, Moscow, Russian Federation
Russian Mining Industry №6/ 2025 p. 187-193

Abstract: The article provides information on a combined method developed for processing images from a video sequence obtained during flights of an unmanned aerial vehicle in underground mine workings. The video sequence was subjected to shot breakdown, during which the differences between the frames comprising the stereoscopic pair were evaluated. This task was addressed using computer vision capabilities. The computer vision algorithms were implemented using the OpenCV library, which was used to develop a software module to analyze the image similarity based on the SSIM and MSE indicators. The study found that the use of computer vision and neural network technologies can significantly improve the quality and accuracy of the mine workings models. Further development of the proposed method consists in developing techniques and gaining the experience for quantitative assessment of the rock mass heterogeneities and describing the shapes of mine workings elements in various locations (in the roof, floor, walls, etc.). The possibility of using the image quality enhancement technologies based on deep learning algorithms is quite promising. A particular area of interest is creation of 3D models. The development and implementation of video-based photogrammetric methods in underground mining practice will contribute to solving tasks such as autonomous monitoring of the support condition in mine workings, refinement of the stope profile during the ore drawing, planning of stoping in adjacent rooms after backfilling operations, hazard detection, and geological analysis with, for instance, refinement of the fracture-system parameters in rock masses among many others.

Keywords: photogrammetry, underground mine workings, mine working model, unmanned aerial vehicle, video imaging, stopes

Acknowledgements: The study was carried out with the support of the Russian Science Foundation, grant No. 25-17-00345, https://rscf.ru/project/25-17-00345/

For citation: Fedotenko V.S., Kirkov A.E., Radchenko D.N., Averin A.P. Development of photogrammetric models based on video survey data of underground mine workings in low-light conditions. Russian Mining Industry. 2025;(6):187–193. (In Russ.) https://doi.org/10.30686/1609-9192-2025-6-187-193

Information about the article

Received: 29.08.2025

Revised: 27.10.2025

Accepted: 10.11.2025

Information about the authors

Viktor S. Fedotenko – Dr. Sci. (Eng.), Leading Researcher, Head of the Department of Design Theory and Geotechnology for Integrated Subsurface Development, Institute of Comprehensive Exploitation of Mineral Resources of the Russian Academy of Sciences, Moscow, Russian Federation; https://orcid.org/0000-0002-2082-6040

Aleksey E. Kirkov – Chief Mine Surveyor, Researcher, Institute of Comprehensive Exploitation of Mineral Resources of the Russian Academy of Sciences, Moscow, Russian Federation

Dmitry N. Radchenko – Cand. Sci. (Eng.), Associate Professor, Leading Researcher, Head of the Laboratory of Theoretical Fundamentals for Mining Systems Design, Institute of Comprehensive Exploitation of Mineral Resources of the Russian Academy of Sciences, Moscow, Russian Federation; https://orcid.org/0000-0003-1821-3840; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Andrey P. Averin – Cand. Sci. (Eng.), Senior Researcher, Institute of Comprehensive Exploitation of Mineral Resources of the Russian Academy of Sciences, Moscow, Russian Federation

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