04. Kazakevich P.P., Yurin A.N. Development of a Graphic Interface Application for the Vision System of the Fruit Sorting Line. Engineering Technologies and Systems

LATEST ISSUE

For readers

For authors

FOR REVIEWERS

SOCIAL NETWORKS

Engineering Technologies and Systems is an open access journal, which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author in accordance with the BOAI definition of open access.

All the materials of the “Engineering Technologies and Systems” journal are made available under a Creative Commons «Attribution» 4.0 license.

Useful Materials

To download article.

DOI: 10.15507/2658-4123.033.202303.356-372

Development of a Graphic Interface Application for the Vision System of the Fruit Sorting Line

Petr P. Kazakevich
Dr.Sci. (Engr.), Professor, Corresponding Member, Deputy Chairman of the Presidium of the National Academy of Sciences of Belarus (66 Nezavisimosti Ave., Minsk 220072, Republic of Belarus), ORCID: https://orcid.org/0000-0002-9102-2816, This email address is being protected from spambots. You need JavaScript enabled to view it.

Anton N. Yurin
Cand.Sci.(Engr.), Associate Professor, Head of Laboratory, Scientific and Practical Center of the National Academy of Sciences of Belarus for Agricultural Mechanization (1 Knorina St., Minsk 220049, Republic of Belarus), ORCID: https://orcid.org/0000-0001-9348-8110, This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract
Introduction. At present, an intuitive graphical interface is an indispensable component of modern agricultural-oriented software products.
Aim of the Article. The research is aimed at improving the efficiency of sorting apples by developing a graphical control interface for a vision system to recognize various defects and sort apples.
Materials and Methods. The authors used methods of analysis, enumeration, comparison and synthesis of modern software solutions.
Results. As a result of the research, there was created a graphical application of the software for the control unit of the machine vision system containing all the necessary tools for managing and optimizing costs when sorting apples into three commercial quality classes.
Discussion and Conclusion. The graphical interface of the machine vision system was used in the line LSP-4 for sorting and packing apples. It was developed by Scientific and Practical Center NAS of Belarus for Agricultural Mechanization in 2020 and successfully passed state acceptance tests.

Keywords: graphical interface, artificial neural network, apple sorting, machine vision, control unit

Funding: The work was carried out as a part of the task No. 5 “Development and use of technological line for sorting and packing applesˮ of the subprogram “Belselkhozmekhanizatsiya‒2025ˮ of the state scientific and technical program “Innovative agro-industrial and food technologiesˮ 2021‒2025.

Acknowledgments: The authors thank the reviewers for their contribution to the peer review of the paper.

Conflict of interest: The authors declare no conflict of interest.

For citation: Kazakevich P.P., Yurin A.N. Development of a Graphic Interface Application for the Vision System of the Fruit Sorting Line. Engineering Technologies and Systems. 2023;33(3):356–372. https://doi.org/10.15507/2658-4123.033.202303.356-372

Authors contribution:
P. P. Kazakevich ‒ scientific management, revision of the text, final conclusions.
A. N. Yurin ‒ concept of the research, research implementation, text writing, final conclusions.

All authors have read and approved the final manuscript.

Submitted 30.03.2023; revised 24.04.2023;
accepted 26.07.2023.

REFERENCES

1. Smirnov I.G., Hort D.O., Kutyrev A.I. Intelligent Technology and Robotic Horticulture Machines. Agricultural Machines and Technologies. 2021;15(4):35–41. https://doi.org/10.22314/2073-7599-2021-15-4-35-41

2. Lovpache Sh.Z., Mamelin Yu.V., Sinitsa S.G., Buzko V.Yu., Mamelina A.S. Development of Methods for Multispectral Differentiation of Natural and Synthetic Materials Based on the Spectral Characteristics of Diffuse Reflection. Izvestiya SPbGETU LETI. 2021;(10):11–17. Available at: https://izv.etu.ru/assets/files/izvestiya-10-2021-11-17.pdf (accessed 29.03.2023). (In Russ., abstract in Eng.)

3. Kazakevich P.P., Yurin A.N., Prokopovich G.A., Technical Perspective System of Apple Defects: Substantiation, Development, Verification. Ves. National Acad. Sciences of Belarus. Ser. Agrarian Sciences. 2021;59(4):488–500. https://doi.org/10.29235/1817-7204-2021-59-4-488-500

4. Khort D.O., Kutyrev A.I., Smirnov I.G., Filippov R.A., Vershinin R.V. Development of Algorithms for a System of Rich Berries of Garden Strawberries with Robotic Picking. Electrical Technologies and Electrical Equipment in the Agro-industrial Complex. 2020;(1):133–141. https://doi.org/10.22314/2658-4859-2020-67-1-133-141

5. Kovalenko T., Solodov A. Game Interface as an Object of Study. The Scientific Heritage. 2020;(45-1):36–42. Available at: https://cyberleninka.ru/article/n/igrovoy-interfeys-kak-obekt-issledovaniya/viewer (accessed 04.04.2022). (In Russ., abstract in Eng.)

6. Kudryavtsev M.A. Methodology for Measuring the Complexity of Perception of the Graphical User Interface. Modern Innovations. 2017;(4):10–12. Available at: https://cyberleninka.ru/article/n/metodika-izmereniya-slozhnosti-vospriyatiya-graficheskogointerfeysa-polzovatelya/viewer (accessed 04.04.2022). (In Russ.)

7. Dudnik M.D. Design of User Interfaces for Data Analysis Software: Overview of Existing Approaches. Vestnik of St. Petersburg State University of Technology and Design. 2022;(2):23–28. Available at: http://publish.sutd.ru/docs/content/vestnik_mu_2_2022.pdf (accessed 29.03.2023). (In Russ., abstract in Eng.)

8. Fedorovа S.V. Determination of a Multi-Criteria Indicator of the Quality of the Graphical Interface of the Hardware-Software Complete Communication Complex. H&ES Research. 2021;13(3):20–27. https://doi.org/10.36724/2409-5419-2021-13-3-20-27

9. Tikhanychev O.V. User Interfaces in Automatic Sources: Development Problems. Software Systems and Computational Methods. 2019;(2):11–22. https://doi.org/10.7256/2454-0714.2019.2.28443

10. Nazarenko N.A., Paderno P.I. Influence of Appearance on the Condition and Health of the Operator. Biotechnosfera. 2009;(6):45–52. Available at: https://cyberleninka.ru/article/n/vliyanie-interfeysa-na-sostoyanie-i-zdorovie-operatora/viewer (accessed 29.03.2022). (In Russ., abstract in Eng.)

11. Konyukhova O.V. Model of the User Interface Management System for the Development of User Interfaces for Graphic Editors. Bulletin of the Oryol State Technical University. Series: Information Systems and Technologies. 2004;(5):82–86. Available at: https://oreluniver.ru/science/journal/isit/archive?p=11 (accessed 29.03.2023). (In Russ., abstract in Eng.)

12. Hort D.O., Kutyrev A.I., Filippov R.A. Computer Vision System for Recognition Strawberries. Novosti nauki v APK. 2019;(3):308–313. (In Russ., abstract in Eng.) https://doi.org/10.25930/2218-855X/080.3.12.2019

13. Azarenko V.V., Komlach D.I., Goldyban V.V., Baranovsky I.A., Prokopovich G.A. Development of a Hinged System for Controlling a Row Cultivator in Automatic Mode. Weight. National Acad. Sciences of Belarus. Ser. Agrarian Sciences. 2021;59(2):232–242. (In Russ., abstract in Eng.) https://doi.org/10.29235/1817-7204-2021-59-2-232-242

14. Goronkov K.A., Rudenko O.V., Usatikov S.V. Database of the Training Sample for High-Precision Recognition of Flat Images of Cereal and Oilseed Varieties. Fundamental Research. 2011;(8):342–346. Available at: https://fundamental-research.ru/ru/article/view?id=27960 (accessed 29.03.2023). (In Russ., abstract in Eng.)

15. Istratova E.E., Pustovskikh D.A. Development and Research of a Biometric Face Recognition System Based on the Application of the Deep Learning Method. International Journal of Open Information Technologies. 2022;10(12):66–74. Available at: https://cyberleninka.ru/article/n/razrabotka-i-issledovanie-biometricheskoy-sistemy-raspoznavaniya-lits-na-osnove-primeneniya-metoda-glubokogo-obucheniya/viewer (accessed 29.03.2023). (In Russ., abstract in Eng.)

16. Arefiev R.A., Zudilova T.V. SOA Design Pattern for User Interfaces for Multiplatform Applications. Software Systems and Computational Methods. 2016;(2):201–209. (In Russ., abstract in Eng.) https://doi.org/10.7256/2305-6061.2016.2.18627

17. Tsai W. T., Shao Q., Li W. Service-Oriented User Interface Modeling and Composition. In: eBusiness Engineering, 2008. ICEBE'08. IEEE International Conference on. IEEE; 2008. P. 21–28. https://doi.org/10.1109/SOCA.2010.5707139

18. Ali M.F., Perez-Quinones M.A., Shell E., et al. Building Multi-Platform User Interfaces with UIML. Computer-Aided Design of User Interfaces III. Springer Netherlands; 2002. Pp. 255–266. https://doi.org/10.48550/arXiv.cs/0111024

19. Ganganagowdar N.V., Gundad A.V. Intelligent Computer Vision System for Vegetables and Fruits Quality Inspection Using Soft Computing Techniques. Agricultural Engineering International. 2019;21(3):171–178. Available at: https://cigrjournal.org/index.php/Ejounral/article/view/5188 (accessed 29.03.2023).

20. Gauch S., Chaffee J., Pretschner A. Ontology-Based Personalized Search and Browsing. Web Intelligence and Agent Systems. 2003;(1):219–234. Available at: https://www.researchgate.net/publication/220298562_Ontology-based_personalized_search_and_browsing (accessed 29.03.2023).

This work is licensed under a Creative Commons Attribution 4.0 License.