Designing and Implementing a Classification Model for Mangoes Based on Size and Ripeness using Image Processing

Authors

An van Vo, Thu Dau Mot University, Binh Duong 75000, VietnamFollow
Hau van Mai, University of Transport and Communications, Hanoi 10000, VietnamFollow
Hung Duy Ha, Wireless Communications Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 70000, VietnamFollow
tam thanh bui, Thu Dau Mot University, Binh Duong 75000, VietnamFollow

Abstract

Image processing is an advanced technology that significantly supports production, identification, and quality control for fruits. This paper uses image processing techniques to develop a mango classification system based on size and ripeness. The system integrates hardware, including an Arduino microcontroller, camera, sensors, actuators, and a user-friendly computer interface for monitoring and control. The classification algorithm extracts key features of the mangoes, such as their color and shape, to categorize them into predefined quality classes. Experimental results demonstrate that the system achieves an accuracy exceeding 90% for both ripeness and size classification, with a productivity level of 300 kg/hour, surpassing the initial target of 250 kg/hour. Furthermore, the system operates reliably under varying lighting conditions, ensuring flexibility and continuous productivity. These advancements highlight the system’s potential to enhance efficiency and quality in fruit processing industries.

References

D.C. Tam, J. Sci. Res. Econ. Dev. Tay Do Univ. 12 (2021).

D. Jhala, A. Bagade, S. Naik, S. Lad, B. Shah, IOSR J. Eng. 4 (2018) 43.

N.T. Thinh, N.D. Thong, H.T. Cong, Int. J. Mach. Learn. Comput. 10 (2020) 374.

U. Tomas, Ganiron Jr., Int. J. Bio-Sci. Bio-Technol. 6 (2014) 31.

N.T. Thinh, N.D. Thong, H.T. Cong, N.T.T. Phong, 2019 7th International Conference on Control, Mechatronics and Automation (ICCMA), Delft, Netherlands, 2019, p.475.

N.D. Thong, N.T. Thinh, H.T. Cong, Int. J. Eng. Technol. 11 (2019) 321.

A. Supekar, M. Wakode, Int. J. Curr. Eng. Technol. 8 (2021) 808.

M. Wankhade, U.W. Hore, Int. J. Adv. Res. Sci. Commun. Technol. 6 (2021) 1390.

J.O.R. Varjão, G.M. Botelho, T.d.S. Almeida, G.A.d.S. Martins, W.G.G. da Silva, Int. J. Adv. Eng. Res. Sci. 6 (2019) 59.

M.F. Mavi, Z. Husin, R.B. Ahmad, Y.M. Yacob, R.S.M. Farook, W.K. Tan, J. Electr. Eng. Comput. Sci. 14 (2019) 859.

M.E. Irhebhude, A.O. Kolawole, F.B. Bugaje, Int. J. Comput. Digit. Syst. 11 (2022) 963.

A.R. Amrutkar, H.B. Jaisingpure, P.A. Bhujade, Int. J. Adv. Res. Ideas Innov. Technol. 4 (2018) 1947.

C.P. Vijay, S.Y. Gupta, Int. J. Comput. Appl. 20 (2021) 16.

Arduino Uno, Farnell, https://www.farnell.com/dat asheets/1682209.pdf.

D. Sahu, C. Dewangan, J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2 (2016) 203.

D. Sahu, R.M. Potdar, Am. J. Art. Intell. 1 (2017) 5.

N.T.T. Nhan, Thesis, University of Information Technology and Communications, Indonesia, 2016.

J. Tang, 2nd International Conference on Computer Engineering and Technology, Chengdu, China, 2010, p.634.

J. Pardede, M.G. Husada, A.N. Hermana, S.A. Rumapea, 2019 International Conference of Computer Science and Information Technology (ICoSNIKOM), Medan, Indonesia, 2019, p.5.

M. Furqan, M. Ikhsan, A. Dalimunthe, Int. J. Inf. Syst. Technol. 5 (2021) 513.

K. Schulze, M. Nagle, W. Spreer, B. Mahayothee, J. Müller, Comput. Electron. Agr. 114 (2015) 269.

F.S.A. Sa’ad, M.F. Ibrahim, A.Y.M. Shakaff, A. Zakaria, M.Z. Abdullah, Comput. Electron. Agr. 115 (2015) 51

Recommended Citation

Vo, An van; Mai, Hau van; Ha, Hung Duy; and bui, tam thanh (2025) "Designing and Implementing a Classification Model for Mangoes Based on Size and Ripeness using Image Processing," Makara Journal of Technology: Vol. 29: Iss. 1, Article 2.
DOI: 10.7454/mst.v29i1.1686
Available at: https://scholarhub.ui.ac.id/mjt/vol29/iss1/2