Krokhmal V., Krokhmal A., Tarasov V., Rudniev Ye. Application of the combined method of raster image recognition in the computer vision system of unmanned vehicles in the mining industry

Details
Parent Category: Geo-Technical Mechanics, 2024
Category: Geo-Technical Mechanics, 2024, Issue 171

Geoteh. meh. 2024, 171, 98-110

https://doi.org/10.15407/geotm2024.171.098

APPLICATION OF THE COMBINED METHOD OF RASTER IMAGE RECOGNITION IN THE COMPUTER VISION SYSTEM OF UNMANNED VEHICLES IN THE MINING INDUSTRY

Krokhmal V. 

Krokhmal A. 

Tarasov V. 

Rudniev Ye. 

Volodymyr Dahl East Ukrainian National University

UDC 622:004.8

Language: English

Abstract. The mining industry is rapidly moving towards the practical implementation of the achievements of the fourth industrial revolution, Mining 4.0, based on the automation of underground mining processes. And smart mines, as a trend of the near future, are already taking shape with the development of technologies for the next stage of mining development - Mining 5.0. The use of autonomous intelligent robots and cobots, self-driving equipment and vehicles in a single production and information space of a smart mine will improve the safety of production processes and mine personnel. The challenging environment of a mine puts specific demands on the development and operation of autonomous robots and monitoring systems in the underground space. Therefore, the problem of eliminating errors in the identification of any stationary and moving objects in the mine requires the development of effective methods for recognising the received images in computer vision systems. Computer vision, as one of the areas of artificial intelligence, allows you to extract useful information from digital images, videos or visual data. The aim of this paper is to study the methods of image processing and analysis and to develop a combined method for recognising dark objects on a light background. The article deals with the problem of integrating innovative technologies into the system of remote monitoring of the technological environment in a mine with the use of robotic means, in particular, unmanned aerial vehicles. The method is based on image processing, then the concept of image enhancement based on appropriate algorithms is considered. Experiments on the recognition and counting of coal particles (ITES Vranov, s.r.o., Slovakia), which are dark objects on a light background, showed the effectiveness of the combined method in changing observation conditions (image size, illumination, object size), adaptability to the use of various technical means of image registration, and flexibility in setting detection parameters. For an image with a size of 600 pixels, which is sufficient to ensure correct measurements, the maximum processing time was 7.3 ms. The size of the error increases with the size of the image, which indicates an increased variability of time when processing large images. The largest share of the processing time is taken up by component filtering (this stage also includes marking the original image), which retains a consistently high percentage of time as the image size increases. The Hough transform and Yen's binarization also have a significant part. Other stages, such as resizing, blurring, masking, have a less significant contribution.

Keywords: mine, security, computer vision, image processing.

 

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About the authors:

Krokhmal Vitalii, Doctoral Student, Volodymyr Dahl East Ukrainian National University (VDEUNU), Kyiv, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0009-0007-6585-1032

Krokhmal Andrii, Master of Science, Volodymyr Dahl East Ukrainian National University (VDEUNU), Kyiv, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0009-0005-5309-8392.

Tarasov Vadym, Doctor of Technical Sciences (D.Sc.), Professor, Head of Faculty of Human Health, Volodymyr Dahl East Ukrainian National University (VDEUNU), Kyiv, This email address is being protected from spambots. You need JavaScript enabled to view it. (Corresponding author),  ORCID 0000-0003-3614-0913

Rudniev Yevhen, Doctor of Technical Sciences (D.Sc.), Associate Professor, Professor of the Department of Electrical Engineering, Professor of the Department of Pharmacy, Production and Technology, Volodymyr Dahl East Ukrainian National University (VDEUNU), Ukraine, Kyiv, This email address is being protected from spambots. You need JavaScript enabled to view it. , ORCID 0000-0002-4236-8407