FUZZY RIPENING MANGO INDEX USING RGB COLOUR SENSOR MODEL

Authors

  • Ab Razak Mansor Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA Kedah.
  • Mahmod Othman Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA Perlis.
  • Mohd Nazari Abu Bakar Faculty of Applied Science, Universiti Teknologi MARA Perlis.
  • Khairul Adilah Ahmad Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA Kedah.
  • Tajul Rosli Razak Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA Perlis.

Keywords:

Mango Grading, Fuzzy System, RGB Colour Sensor

Abstract

Currently, the mango ripeness classification is determined manually by human graders according to a particular procedure. This method is inconsistent and subjective in nature because each grader has different techniques. Thus, it affects the quantity and quality of the mango fruit that can be marketed. In this project, a new model for classifying mango fruit is developed using the fuzzy logic RGB sensor colour model build in the MATLAB software. The grading system was programmed with a colour sensor to analyze the mango fruit ripening index. The decision making process uses fuzzy logic to train the data and also to classify or categorize the mango fruit. The model developed is able to distinguish or separate the three different classes of mango fruit. The proposed model is able to distinguish the three different classes of mango fruit automatically with more than 85% accuracy.

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References

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Published

07-09-2021

How to Cite

Ab Razak Mansor, Mahmod Othman, Mohd Nazari Abu Bakar, Khairul Adilah Ahmad, & Tajul Rosli Razak. (2021). FUZZY RIPENING MANGO INDEX USING RGB COLOUR SENSOR MODEL. Researchers World - International Refereed Social Sciences Journal, 5(2), 01–10. Retrieved from https://researchersworld.com/index.php/rworld/article/view/764

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