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AGRICULTURE MECHANIZATION AND ELECTRIFICATION

ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD

Jahfer Alikhanov 1 , Aidar Moldazhanov 1 , Dmitry Zinchenko 1 , Alisher Nurtuleuov 1 , Sagi Soltanbekov 2 , Zhanar Kadirsizova 3

1 NJSC «Kazakh National Agrarian Research University» ; 2 "Kazakh Research Institute of Fruit and Vegetable Growing" LLP; 3 LLP "Kazakh Research Institute of Horticulture"

doi.org/10.37884/1-2024/28 pp. 288-299 Admitted 30.01.2024 Published 29.03.2024

Abstract

This article is devoted to a study aimed at the development and thorough analysis of an algorithm and software for automatically determining the parameters of apples, based on the analysis of their images using computer vision. The methodology described in the article is based on the analysis of apple images using the OpenCV computer vision library implemented in the Python programming language. The developed algorithm allows you to automatically determine a number of key characteristics of apples, including their diameter, height, area, percentage of red color on the surface and identification of possible external defects. As part of the study, the qualitative characteristics of apples were analyzed based on their external parameters. This made it possible to develop specialized procedures for the automated determination of these parameters using image analysis. In the process of verifying the effectiveness of the technique, experiments were conducted in which the results obtained by traditional measurement methods were compared with the results obtained on the basis of an automated digital installation. The results obtained during the study confirmed the practical coincidence of the values of the diameter and height of the fetus, measured with a caliper and determined using the developed program. In addition, the developed algorithm and program make it possible to determine not only the basic parameters of apples, but also to analyze the cross-sectional area and the percentage of red color on their surface. As a result, the developed method makes it possible to significantly speed up the process of determining the parameters of apples compared to traditional manual methods, which has been proven by experimental results.

apple, algorithm, program, diameter, height, area, accuracy, performance, installation.

01 Introduction

The full text of the article is available for download in PDF format on the right panel.

02 References

  1. 1. https://kaztag.kz/ru/news/defitsit-mestnykh-yablok-v-kazakhstane-obeshchayut-ustranit-tolko-k-2024-godu
  2. 2. Near-Infrared Spectroscopy in Food Science and Technology. Ed. by Y. Ozaki, W. Fr. Mc Clure, A. A. Christy, John Wiley and sons Inc., New Jersey, 2007.
  3. 3. Roberts C.A., J Workman, J.B. Reeves ІІІ, Near-Infrared Spectroscopy in Agriculture, IM Publications, UK, 2004.
  4. 4. Bhatt, A.K., Pant, D., 2015. Automatic apple grading model development based on back propagation neural network and machine vision, and its performance evaluation. AI & Soc. 30 (1), 45–56
  5. 5. M.M. Sofu , O. Erb, M.C. Kayacan , B. Cetisi. 2016. Design of an automatic apple sorting system using machine vision. Computers and Electronics in Agriculture 127 (2016) 395–405
  6. 6. Anand Kumar Pothula a, Zhao Zhang b, Renfu Lu c, Evaluation of a new apple in-field sorting system for fruit singulation, rotation and imaging Computers and Electronics in Agriculture 208 (2023) 107789 https://doi.org/10.1016/j.compag.2023.107789.
  7. 7. Payman Moallem a,b,*, Alireza Serajoddin c, Hossein Pourghassem d,c Computer vision-based apple grading for golden delicious apples based on surface features Information processing in agriculture 4 (2017) 33–40 https://doi.org/10.1016/j.inpa.2016.10.003.
  8. 8. Жиркова А.А., Балабанов П.В., Дивин А.Г., Егоров А.С., Макарова В.С. Система оптического контроля качества яблок / А.А. Жиркова, П.В. Балабанов, А.Г. Дивин, А.С. Егоров, В.С. Макарова [Текст] // Труды Международного симпозиума «Надежность и качество». — Пенза, 2021. — С. 20-23.
  9. 9. Балабанов П.В., Жиркова А.А., Дивин А.Г., Егоров А.С., Мищенко С.В., Шишкина Г.В. Информационно-измерительная система для управления процессом сортировки овощей и фруктов [Текст] / П. В. Балабанов, А.А. Жиркова, А.Г. Дивин, А.С. Егоров, С.В. Мищенко, Г.В. Шишкина // Вестник Тамбовского государственного технического университета. — 2022. — № 28 (4). — С. 526-533.
  10. 10. Родиков, С. А. Анализ цветности кожицы яблок и содержание а них хлорофилла / С. А. Родиков [Текст] // Материалы научн.-практ. конференции. — Мичуринск: Изд-во Мичуринского ГАУ, 2022. — С. 106-107.
  11. 11. Alikhanov J, Stanislav M. Penchev, Tsvetelina D. Georgieva., Moldazhanov A., Plamen I. Daskalov. An indirect approach for egg weight sorting using image processing. Journal of Food Measurement and Characterization. Springer US. -2018. – V. 12 – Iss. 1 P. 87-93 IF(0.536)
  12. 12. Нуртулеуов*, А., Молдажанов, А., Кулмахамбетова, А., & Зинченко, Д. (2021). Обоснование метода и алгоритма определения показателей качества яблок и автоматической сортировки их на категории. Izdenister Natigeler, (3 (91), 125–133. https://doi.org/10.37884/3-2021/14
  13. 13. Автоматизация сортировки и отбраковки [Электронный ресурс]. - Режим доступа: http://www.mkoi.org/366/367/373/
  14. 14. OpenCV шаг за шагом. Поиск объекта по цвету – RGB [Электронный ресурс].-Режим доступа: http://robocraft.ru/blog/computervision/365.html

Citation Links

[1]2024. ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. Izdenister natigeler. 1 (101) (Mar. 2024), 288–299. DOI:https://doi.org/10.37884/1-2024/28.
(1)ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. Izdenister natigeler 2024, No. 1 (101), 288-299. https://doi.org/10.37884/1-2024/28.
ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. (2024). Izdenister Natigeler, 1 (101), 288-299. https://doi.org/10.37884/1-2024/28
ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. Izdenister natigeler, [S. l.], n. 1 (101), p. 288–299, 2024. DOI: 10.37884/1-2024/28. Disponível em: https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/484. Acesso em: 15 sep. 2026.
“ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD”. 2024. Izdenister Natigeler, no. 1 (101) (March): 288-99. https://doi.org/10.37884/1-2024/28.
“ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD” (2024) Izdenister natigeler, (1 (101), pp. 288–299. doi:10.37884/1-2024/28.
[1]“ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD”, Izdenister natigeler, no. 1 (101), pp. 288–299, Mar. 2024, doi: 10.37884/1-2024/28.
“ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD”. Izdenister Natigeler, no. 1 (101), Mar. 2024, pp. 288-99, https://doi.org/10.37884/1-2024/28.
“ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD”. Izdenister natigeler, no. 1 (101) (March 29, 2024): 288–299. Accessed September 15, 2026. https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/484.
1.ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. Izdenister natigeler [Internet]. 2024 Mar. 29 [cited 2026 Sep. 15];(1 (101):288-99. Available from: https://agrosoil.kaznaru.edu.kz/index.php/research/article/view/484
1.ALGORITHM AND PROGRAM FOR DETERMINING THE PARAMETERS OF THE APPLE DIGITAL METHOD. Izdenister natigeler. 2024;(1 (101):288-299. doi:10.37884/1-2024/28