Optimization of contrast enhancement in images obtained in mines

Optimization of contrast enhancement in images obtained in mines through automation of evaluation of image quality factors is discussed in the article. The IDEF0 notations before and after optimization are presented. The methods and algorithms of contrast enhancement used in processing of digital images from miner lamp cameras are reviewed. The features of digital images from miner lamp cameras, and their brightness are discussed. The histograms of brightness of the images before and after their processing using the test methods are given. The contrast quality factors of the images are calculated. The recommendations on automated selection of quality factors by the contrast enhancement system are made.

Keywords: industrial video surveillance, IDEF0 function modeling method, digital image, brightness histogram, image processing, contrast, mine video data.
For citation:

Zaitseva E. V., Kochneva A. A., Katuntsov E. V. Optimization of contrast enhancement in images obtained in mines. MIAB. Mining Inf. Anal. Bull. 2025;(7):115-130. [In Russ]. DOI: 10.25018/0236_1493_2025_7_0_115.

Acknowledgements:
Issue number: 7
Year: 2025
Page number: 115-130
ISBN: 0236-1493
UDK: 004.932.4
DOI: 10.25018/0236_1493_2025_7_0_115
Article receipt date: 27.09.2023
Date of review receipt: 04.04.2025
Date of the editorial board′s decision on the article′s publishing: 10.06.2025
About authors:

E.V. Zaitseva1, Cand. Sci. (Eng.), Assistant Professor, e-mail: Zaytseva_EV@pers.spmi.ru, ORCID ID: 0000-0002-7944-0468,
A.A. Kochneva1, Cand. Sci. (Eng.), Assistant Professor, e-mail: Kochneva_AA@pers.spmi.ru, ORCID ID: 0000-0002-8189-782X,
E.V. Katuntsov1, Cand. Sci. (Eng.), Assistant Professor, e-mail: Katuntsov_EV@pers.spmi.ru, ORCID ID: 0000-0001-8345-0979,
1 Empress Catherine II Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.

 

For contacts:

E.V. Zaitseva, e-mail: Zaytseva_EV@pers.spmi.ru.

Bibliography:

1. Novikov A. V., Panevnikov K. V., Pisarev I. V. Multifunctional security system for coal mines — visualization of events (mining processes) from the miner's workplace. Russian Mining Industry Journal. 2021, no. 5, pp. 65—69. [In Russ]. DOI: 10.30686/1609-9192-2021-5-65-69.

2. Ol’t Yu., Maksarov V. V., Makhov V. E. Intelligence systems for quality assessment of threaded surfaces and flaw monitoring based on digital light field recording. Russian Journal of Nondestructive Testing. 2020, vol. 56, no. 11, pp. 915—926. DOI: 10.1134/S1061830920110054.

3. Koteleva N., Valnev V. Automatic Detection of Maintenance Scenarios for Equipment and Control Systems in Industry. Applied Sciences (Switzerland). 2023, vol. 13, no. 24, article 12997. DOI: 10.3390/app132412997.

4. Rudakov M. L., Rabota E. N., Kolvakh K. A. Assessment of the individual risk of fatal injury to coal mine workers during collapses. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2020, vol. 4, pp. 88—93. DOI: 10.33271/nvngu/2020-4/088.

5. Nepsha F. S., Voronin V. A., Liven A. S., Korneev A. S. Feasibility study of using cogeneration plants at Kuzbass coal mines. Journal of Mining Institute. 2023, vol. 259, pp. 141—150. [In Russ]. DOI: 10.31897/PMI.2023.2.

6. Buzmakov S. A., Sannikov P. Yu., Kuchin L. S., Igosheva E. A., Abdulmanova I. F. The use of unmanned aerial photography for interpreting the echnogenic transformation of the natural environment during the oil field operation. Journal of Mining Institute. 2023, vol. 260, pp. 180—193. [In Russ]. DOI: 10.31897/PMI.2023.22.

7. Makhovikov A. B., Kryltsov S. B., Matrokhina K. V., Trofimets V. Y. Secured communication system for a metallurgical company. Tsvetnye Metally. 2023, no. 4, pp. 5—13. [In Russ]. DOI: 10.17580/tsm.2023.04.01.

8. Zakharov V. N., Gvishiani A. D., Vaisberg L. A., Dzeranov B. V. Big data and sustainable functioning of geotechnical systems. Gornyi Zhurnal. 2021, no. 11, pp. 45—52. [In Russ]. DOI: 10.17580/ gzh.2021.11.06.

9. Litvinenko V. S., Bowbrick I., Naumov I. A., Zaitseva Z. Global guidelines and requirements for professional competencies of natural resource extraction engineers: Implications for ESG principles and sustainable development goals. Journal of Cleaner Production. 2022, vol. 338, pp. 1—9. DOI: 10.1016/j.jclepro.2022.130530.

10. Valkov V. A., Vinogradov K. P., Valkovа E. O., Mustafin M. G. Creating highly informative rasters based on laser scanning and aerial photography data. Geodesy and Cartography. 2022, vol. 989, no. 11, pp. 40—49. [In Russ]. DOI: 10.22389/0016-7126-2022-989-11-40-49.

11. Zhang H., Tao P., Meng X., Liu M., Liu X. An optimum deployment algorithm of camera networks for open-pit mine slope monitoring. Sensors. 2021, vol. 21, no. 4, article 1148. DOI: 10.3390/ s21041148.

12. Obukhova N. A., Baranov P. S., Motyko A. A., Chirkunova A. A., Pozdeev A. A. Restoration of low-contrast texts of archival documents based on the use of hyperspectral technologies. Tsifrovaya obrabotka signalov i ee primenenie DSPA–2023. Doklady XXV Mezhdunarodnoy konferentsii [Digital signal processing and its application DSPA–2023. Reports of the XXV International Conference], Moscow, 2023, pp. 210—214. [In Russ].

13. Pryakhin E. I., Troshina E. Y. Degradation induced by thermal and chemical on matrix codes installed on brass and aluminium alloy parts by laser. Tsvetnye Metally. 2022, no. 7, pp. 87—91. [In Russ]. DOI: 10.17580/tsm.2022.07.10.

14. Gruzman I. S., Kirichuk V. S., Kosykh V. P., Peretyagin G. I., Spektor A. A. Tsifrovaya obrabotka izobrazheniy v informatsionnykh sistemakh [Digital image processing in information systems], Novosibirsk, NGTU, 2000, 156 p.

15. Gonsales R., Vuds R. Tsifrovaya obrabotka izobrazheniy [Digital image processing], Moscow, Tekhnosfera, 2005, 1072 p.

16. Sergeev M. B., Soloviev N. V., Stadnik A. I. Methods for increasing the contrast of raster images for digital video processing systems. Information and Control Systems. 2007, no. 1 (26), pp. 2—7. [In Russ].

17. Mazakov E. From the history of cybernetics on the example of the department of information systems and computer engineering of the mining university. Voprosy Istorii. 2022, no. 5(1), pp. 107—117. [In Russ]. DOI: 10.31166/VoprosyIstorii202205Statyi01.

18. Zakhlebin A. S., Kalibekov A., Kuryachiy M. I. Construction of a georeferenced orthophotomap of a terrain site based on images from a television camera of a helicopter-type UAV. Electronic means and control systems. Elektronnye sredstva i sistemy upravleniya. Materialy dokladov Mezhdunarodnoy nauchno-prakticheskoy konferentsii [Electronic tools and control systems. Materials of the reports of the International Scientific and Practical Conference], 2020, no. 1-2, pp. 187—189. [In Russ].

19. Sytko I. I., Makhov V. E. Study of dynamic properties of measuring equipment at the design stage. Journal of Physics: Conference Series. 2021, vol. 1728, no. 1, article 012020. https://iopscience. iop.org/article/10.1088/1742-6596/1728/1/012020.

20. Movchan A. K., Kapustin V. V., Kuryachiy M. I., Chaldina E. S. Methods and algorithms for precision range measurement by active-pulse television measuring systems. Proceedings of TUSUR University. 2020, vol. 23, no. 2, pp. 7—14. [In Russ]. DOI: 10.21293/1818-0442-2020-23-2-7-14.

21. Motyko A. A., Chirkunova A. A., Baranov P. S., Obukhova N. A. Hyperspectral technology in state of the art computer vision application. Seminar on Information Computing and Processing (ICP), 2023, pp. 1—4. DOI: 10.1109/ICP60417.2023.10397293.

22. Chaldina E. S., Movchan A. K., Kapustin V. V., Kuryachiy M. I. Multi-area range measurement method using active—pulse television measuring systems. 21th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM-2020). 2021, no. 21, pp. 293—297. DOI: 10.1109/EDM49804.2020.9153500.

23. Brooks C. N., Dobson R. J., Dean D. B., Banach D., Oommen T., Havens T. C., Ahlborn T., Cook S. J., Clover A. Evaluating the use of unmanned aerial vehicles for transportation purposes. Michigan Department of Transportation, Michigan, USA, 2015. Report No. RC-1616, 201 р.

24. Potapov A. I., Makhov V. E., Smorodinskii Y. G., Manevich E. Y. Smart-camera-based linear sizing. Russian Journal of Non-destructive Testing. 2019, vol. 55, no. 7, pp. 524—532.

25. Temkin I., Myaskov A., Deryabin S., Konov I., Ivannikov A. Design of a digital 3D model of transport—technological environment of open-pit mines based on the common use of telemetric and geospatial information. Sensors. 2021, vol. 21, no. 18, article 6277. DOI: 10.3390/s21186277.

26. Chirkunova A. A. Methods for increasing the contrast sensitivity of the image sensor. 2017 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). 2017, pp. 1—4. DOI: 10.1109/EIConRus.2017.7910641.

27. Arena F., Pau G., Severino A. An overview on the current status and future perspectives of smart cars. Infrastructures. 2020, vol. 5, no. 7, article 53. DOI: 10.3390/infrastructures 5070053.

28. Kamenskiy A. V. High-speed recursive-separable image processing filters. Computer Optics. 2022, vol. 46, no. 4, pp. 659—665.

29. Krasil'nikov N. N. Tsifrovaya obrabotka izobrazheniy [Digital image processing], Moscow, Vuzovskaya kniga, 2001, 320 p.

30. Shapiro L., Stockman J. Komp'yuternoe zrenie [Computer vision], Moscow, BINOM, 2006, 752 p.

31. Vostrikov A., Sergeev M., Balonin N., Chernyshev S. В. Digital masking using mersenne matrices and their special images. Procedia Computer Science. Knowledge-Based and Intelligent Information and Engineering Systems: Proceedings of the 21st International Conference. 2017, pp. 1151— 1159. DOI: 10.1016/j.procs.2017.08.156.

32. Vostrikov A. A., Sergeev M. B., Litvinov M. Yu. Masking digital visual information: term and basic definitions. Information and control systems. 2015, no. 5 (78), pp. 116—123. [In Russ]. DOI: 10.15217/issn1684-8853.2015.5.116.

33. Mikhailov V. V., Kolpashchikov L. A., Sobolevsky V. A., Soloviev N. V., Yakushev G. K. Methodological approaches and algorithms for animal recognition and counting on aerial photographs. Information and Control Systems. 2021, no. 5 (114), pp. 20—32. [In Russ]. DOI: 10.31799/1684-88532021-5-20-32.

34. Ubozhenko D. Yu., Zakutaev A. A., Shirobokov V. V. Study of issues of unification of calibration support for quantum-optical and radar equipment. News of the Tula state university. Sciences of Earth. 2021, no. 6, pp. 244—250. [In Russ].

35. Podgornova Yu. A., Sadykov S. S., Samandarov I. R., Vorontsov S. A. Study of criteria for recognition of benign diseases on mammograms. Optiko-elektronnye pribory i ustroystva v sistemakh raspoznavaniya obrazov i obrabotki izobrazheniy. Materialy XVI Mezhdunarodnoy nauchno-tekhnicheskoy konferentsii [Optoelectronic devices and devices in image recognition and image processing systems. Proceedings of the XVI International Scientific and Technical Conference], Kursk, 2021, pp. 279—281. [In Russ].

36. Podgornova Yu. A., Sadykov S. S. Comparative analysis of segmentation algorithms for the allocation of microcalcifications on mammograms. CEUR Workshop Proceedings. Proceedings of the 5th Information Technology and Nanotechnology-2019: Image Processing and Earth Remote Sensing. 2019, pp. 122—127. DOI: 10.18287/1613-0073-2019-2391-121-127.

Подписка на рассылку

Подпишитесь на рассылку, чтобы получать важную информацию для авторов и рецензентов.