Issue №: 1 (132)
The journal presents the results of scientific research and addresses current issues in the development and improvement of agricultural equipment and technologies, particularly in the design, production, and operation of machines and technical systems in the agro-industrial complex, including aspects of their efficient functioning.
AUTOMATION OF THE PROCESSING OF IMAGES OBTAINED WITH THE HELP OF AGRICULTURAL DRONES TAKING INTO ACCOUNT CONDITIONS OF LIMITED VISIBILITY
Oleksandr VOZNYAK – сandidate of Science (Engineering), Associate Professor of the Department of Electric Power Engineering, Electrical Engineering and Electromechanics of Vinnitsa National Agrarian University (3 Soniachna St., Vinnitsa, 21008, Ukraine, email: alex.voz1966@gmail.com, https://orcid.org/0000-0002-0986-6869).
Volodymyr RUTKEVYCH – Candidate of Technical Sciences, Senior Lecturer of Department of machines and equipment of agricultural production of Vinnytsia National Agrarian University (St. Soniachna, 1, Vinnytsia, Ukraine, 21008, e-mail: luts@vsau.vin.ua, https://orcid.org/0000-0002-6366-7772).
Valerii OSTAPENKO – postgraduate Department «Machinery and Equipment of Agricultural Production» of the Vinnytsia National Agrarian University (3, Solnychna str., Vinnytsia, Ukraine, 21008, e-mail:Ostapenko@ukr.net, https://orcid.org/0009-0004-2825-7227).
Roman KHARCHENKO – Master's Degree Holder, Faculty of Engineering and Technology, Vinnytsia National Agrarian University (3 Sonyachna Street, Vinnytsia, 21008, Ukraine, email: r.h.1998@gmail.com).
The paper proposes new, more effective algorithms for the analysis and pre-processing of images obtained using drone cameras in order to automate processes in agriculture. A detailed analysis of modern methods of pre-processing images was conducted in the Matlab environment, and the possibilities of using this tool to improve the quality of digital images were considered. Based on the research results, software was developed that implements a number of advanced processing methods, in particular, contrast enhancement, noise removal, and adaptive filtering. The proposed algorithms allow for significantly improving the quality of images in low light conditions, which is especially relevant for the use of unmanned aerial vehicles in variable weather conditions, in particular in the morning, evening, or in cloudy weather. The developed methods are based on new approaches to improving the statistical characteristics of images, choosing an adequate noise model, and implementing low-frequency filtering that takes into account the specifics of the agricultural environment. The implementation of algorithms in the software package showed a significant improvement in image quality compared to traditional methods. The implementation of such solutions in the navigation and analytical systems of drones used in the agricultural sector will allow to increase the accuracy of collecting and analyzing information about the condition of crops, soil and other agricultural information. This, in turn, will contribute to increasing the efficiency of management, saving resources, reducing the environmental load, as well as forming a modern approach to agricultural production management with the involvement of remote sensing technologies.
1. Vozniak, O. M., Shtuts, A. A., Bulyha, A. I., & Kharchenko, R. Ye. (2023).Doslidzhennia ta udoskonalennia protsesu obrobky zobrazhen navihatsiinoi systemy silskohospodarskykh mashyn z urakhuvanniam umov obmezhenoi vydymosti. Tekhnika, enerhetyka, transport APK, 4(123), 120–131.https://doi.org/10.37128/2520-6168-2023-4-13 [in Ukranian].
2. Rutkevych, V. S., & Ostapenko, V. A. (2024). Rozroblennia vysivnoi systemy posivnoho kompleksu dlia vnutrishno-hruntovoho dyferentsiiovanoho mineralnoho udobrennia z odnochasnoiu sivboiu zernovykh kultur. Visnyk Khmelnytskoho natsionalnoho universytetu. Seriia: Tekhnichni nauky, 1(330), 264–270. https://doi.org/10.31891/2307-5732-2024-331-40 [in Ukranian].
3. Rutkevych, V., Ostapenko, V., & Kazhuro, M. (2024). Teoretychne doslidzhennia umov roboty dozuiuchykh robochykh orhaniv posivnoho kompleksu dlia dyferentsiiovanoho vnesennia dobryv. Visnyk Khmelnytskoho natsionalnoho universytetu. Seriia: Tekhnichni nauky, 4(339), 91–96. https://doi.org/10.31891/2307-5732-2024-339-4-14 [in Ukranian].
4. Voznyak, O., Polievoda, Y., Kupchuk, I., Trukhanska, O., Shvets, L., & Zamrii, M. (2023). Development of object detection algorithm in halftone images. Przegląd Elektrotechniczny, 99(11), 192–195. https://doi.org/10.15199/48.2023.11.33 [in English].
5. Tsurkan, O., Kupchuk, I., Polievoda, Y., Wozniak, O., Hontaruk, Y., & Prysiazhniuk, Y. (2022). Digital processing of one-dimensional signals based on the median filtering algorithm. Przegląd Elektrotechniczny, 98(11), 51–56. https://doi.org/10.15199/48.2022.11.08 [in English].
6. Mavridou, E., Vrochidou, E., Papakostas, G. A., Pachidis, T., & Kaburlasos, V. G. (2019). Machine vision systems in precision agriculture for crop farming. Journal of Imaging, 5(12), 89. https://doi.org/10.3390/jimaging5120089 [in English].
7. Kamilaris, A., & Prenafeta-Boldú, F. X. (2018). Deep learning in agriculture: A survey. Computers and Electronics in Agriculture, 147, 70–90. https://doi.org/10.1016/j.compag.2018.02.016. [in English].
8. Ghazal, S., Said, M., Khamis, A., & El-Sappagh, S. (2024). Computer vision in smart agriculture and precision farming: A survey. Smart Agricultural Technology, 8, 100487. https://doi.org/10.1016/j.atech.2024.100487 [in English].
9. Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674. https://doi.org/10.3390/s18082674 [in English].
10. Lopez, C. P. (2014). MATLAB optimization techniques. Apress. https://doi.org/10.1007/978-1-4842-0292-0 [in English].
11. Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge University Press. https://doi.org/10.1017/CBO9780511804441 [in English].
12. Polikar, R. (1999). The wavelet tutorial. Computers in Science & Engineering, 1(2), 18–26. https://doi.org/10.1109/5992.790641 [in English].
13. Kvashuk, D. M., & Yerokhin, R. O. (2019). Overview of the possibilities of machine vision application in agriculture. Agrosvit, (7), 35–40. https://doi.org/10.32702/2306-6792.2019.7.35 [in Ukranian].
14. Kvashuk, D. M., & Yerokhin, R. O. (2019). Overview of the possibilities of machine vision application in agriculture. Agrosvit, (7), 35–40. https://doi.org/10.32702/2306-6792.2019.7.35 [in Ukranian].
15. Antoshchuk, S. G., Kunup, T. V., Lytvynenko, V. I., & Danchuk, O. V. (2025). Using large language models for video processing in the agricultural industry. Applied Aspects of Information Technology, 8(1), 88–101. https://doi.org/10.15276/aait.08.2025.7 [in Ukranian].
16. Apunevych, I. P. (2024). Artificial intelligence as a driver of change in modern agriculture. Ahrobiolohiia, (2), 6–13. https://doi.org/10.33245/2310-9270-2024-191-2-6-13 [in Ukranian].
17. Feng, L., Zhang, H., Li, X., & Chen, Y. (2025). Application of navigation technology in agricultural machinery: From assisted driving to intelligent navigation. Smart Agricultural Technology, 11, 100821. https://doi.org/10.1016/j.atech.2025.100821 [in English].
18. Kuzmenko, V. F., Veselovska, N. R., Rutkevych, V. S., Shargorodskiy, S. A., & Kholodiuk, O. V. (2025). Modeling of an adaptive hydraulic drive system for the cutting mechanism of a stem feed loader. Journal of Engineering Sciences, 12(2), F1–F11. https://doi.org/10.21272/jes.2025.12(2).f1 [in English].
About journal
The magazine "Engineering, Energy, Transport AIC" is included in the list of scientific professional editions of Ukraine on technical sciences
(Category "Б", Order of the Ministry of Education and Science of Ukraine dated 02.07.2020 №886)
According to the decision of National Council of Television and Radio Broadcasting of Ukraine from 25.04.2024 No. 1337 the scientific journal «Engineering, Energy, Transport AIC» has the ID of the Media R30-05173.
The journal "Engineering, Energy, Transport AIC" is indexed according to the following databases and catalogs:
Certificate of state registration of mass media: No. 21906-11806 P dated 03/12/2016.
Founder of the journal: Vinnytsia National Agrarian University
Type of publication: journal
Kind of publication: scientific
Publication status: domestic
Year of foundation: 1997
Periodicity: 4 times per year
Volume: 18-20 conv. print. sheet (А4)
ISSN: 2520-6168 (print version), (online version)
Language of publication: (mixed languages) Ukrainian, English
The sphere of distribution and category of readers: national, foreign, faculty, scientists, entrepreneurs.
The periodical edition is included to the List of scientific professional publications of Ukraine on technical sciences, approved by order of the Ministry of Education and Science of Ukraine in 05.16.2016, No. 515.
The journal "Engineering, Energy, Transport AIC" is included in the "Catalog of Ukrainian Publications".
Subscription to the journal can be issued in each post office. The subscription index is 99720.
Technology, energy, agriculture transport AIC is a scholarly professional journal with a long-standing history and stable academic tradition, reflecting the evolution of engineering and technical sciences within the agro-industrial sector of Ukraine.
The journal was founded in 1997 under the title Bulletin of Vinnytsia State Agricultural Institute. According to the Resolution of the Presidium of the Higher Attestation Commission of Ukraine dated September 11, 1997, the publication obtained the status of a professional scientific journal, which enabled the publication of the main results of doctoral and candidate dissertations in technical sciences. From its inception, the journal positioned itself as an academic platform for addressing current issues of mechanization, electrification, and technical support of agricultural production.
During 2001–2014, the journal was published under the title Proceedings of Vinnytsia National Agrarian University. Series: Technical Sciences (State Registration Certificate of Print Media KV No. 16644-5116 PR dated April 30, 2010). Throughout this period, a systematic approach to the selection and peer review of scientific manuscripts was established, the thematic scope of publications was expanded, and continuity of scientific directions as well as the development of sectoral engineering schools was ensured.
Since 2015, the journal has been published under its current title, Technology, energy, agriculture transport AIC (State Registration Certificate No. 21906-11806 R dated March 12, 2016). The change of title reflected the expansion of the journal’s thematic coverage and its orientation toward interdisciplinary research in mechanical engineering, energy systems, electrical engineering, transport technologies, automation, and digital solutions for the agro-industrial complex.
The journal consistently adheres to the principles of open science. All published materials are distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), ensuring open access to research results provided proper attribution to the authors and the original publication is maintained.
At present, Technology, energy, agriculture transport AIC is an authoritative professional scientific journal (Category B), providing a platform for the publication of fundamental and applied research results, promoting the integration of education, science, and industry, and contributing to the advancement of engineering and technological support of the agro-industrial complex of Ukraine.
