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IJMLC 2020 Vol.10(2): 374-380 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.2.945

Sorting and Classification of Mangoes based on Artificial Intelligence

Nguyen Truong Thinh, Nguyen Duc Thong, and Huynh Thanh Cong

Abstract—For each type of mango, there are different colors, weights, sizes, shapes and densities. Currently, classification based on the above features is being carried out mainly by manuals due to farmers' awareness of low accuracy, high costs, health effects and high costs, costly economically inferior. This study was conducted on three main commercial mango species of Vietnam as Cat Chu, Cat Hoa Loc and Statue of green skin to find out the method of classification of mango with the best quality and accuracy. Research on mango classification based on the color and volume being conducted does not meet the quality of commercial mangoes and the accuracy is not high. Therefore, a method of mango classification is most effective. In this study, we have proposed and implemented methods, using algorithms to analyze the content combining statistical methods based on image processing techniques to identify commercial mangoes in Vietnam. The main content of this study is to develop an efficient algorithm to design mango classification system with high quality and accuracy. The goal of the study is to create a system that can classify mangoes in terms of color, volume, size, shape and fruit density. The classification system using image processing incorporates artificial intelligence including the use of CCD cameras, C language programming, computer vision and artificial neural networks. The system uses the captured mango image, processing the split layer to determine the mass, volume and defect on the mango fruit surface. Determine the percentage of mango defects to determine the quality of mangoes for export and domestic or recycled mangoes. This article is about the development of an automatic mango classification system to control and evaluate mango quality before packaging and exporting to the market. It is in the research, design and fabrication of mango classification model and the completion of an automatic mango classification system using image processing technology combining artificial intelligence.

Index Terms—Fruit classification, mango sorting, image processing, artificial intelligence, computer vision.

Nguyen Truong Thinh is with the Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam (e-mail: thinhnt@hcmute.edu.vn).
Nguyen Duc Thong is with Dong Thap University, Vietnam (e-mail: ndthong@dthu.edu.vn).
Huynh Thanh Cong is with Vietnam National University, Ho Chi Minh City, Vietnam (e-mail: htcong@vnuhcm.edu.vn).


Cite: Nguyen Truong Thinh, Nguyen Duc Thong, and Huynh Thanh Cong, "Sorting and Classification of Mangoes based on Artificial Intelligence," International Journal of Machine Learning and Computing vol. 10, no. 2, pp. 374-380, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net

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