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A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach

To increase the quality of palm oil means to accurately grade the oil palm fresh fruit bunches (FFB) for processing. In this paper, HSI color model was used to determine the relationship between FFB ' s color with the underipe and ripe category so that the grading system could be accurately don...

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Main Authors: Shabdin, Muhammad Kashfi, Mohamed Shariff, Abdul Rashid, Johari, Mohd Nazrul Azlan, Saat, Nor Kamilah, Abbas, Zulkifly
Format: Article
Language:English
Published: IOP Publishing 2016
Online Access:http://psasir.upm.edu.my/id/eprint/54942/1/A%20study%20on%20the%20oil%20palm%20fresh%20fruit%20bunch%20%28FFB%29%20ripeness%20detection%20by%20using%20Hue%2C%20Saturation%20and%20Intensity%20%28HSI%29%20approach.pdf
http://psasir.upm.edu.my/id/eprint/54942/
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spelling my.upm.eprints.549422018-06-12T08:20:14Z http://psasir.upm.edu.my/id/eprint/54942/ A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach Shabdin, Muhammad Kashfi Mohamed Shariff, Abdul Rashid Johari, Mohd Nazrul Azlan Saat, Nor Kamilah Abbas, Zulkifly To increase the quality of palm oil means to accurately grade the oil palm fresh fruit bunches (FFB) for processing. In this paper, HSI color model was used to determine the relationship between FFB ' s color with the underipe and ripe category so that the grading system could be accurately done. From the analysis manipulation, a formula was generated and applied to the data obtained. The by linear regression in the data shows an average success rate at 45% accuracy for oil palm ripeness detection. Artificial Neural Network (ANN) however return a better accuracy result for both underipe and ripe categories which are 60% and 80% respectively. This yield an overall accuracy of 70%. This can be increased more by improving the grading system. IOP Publishing 2016 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/54942/1/A%20study%20on%20the%20oil%20palm%20fresh%20fruit%20bunch%20%28FFB%29%20ripeness%20detection%20by%20using%20Hue%2C%20Saturation%20and%20Intensity%20%28HSI%29%20approach.pdf Shabdin, Muhammad Kashfi and Mohamed Shariff, Abdul Rashid and Johari, Mohd Nazrul Azlan and Saat, Nor Kamilah and Abbas, Zulkifly (2016) A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach. IOP Conference Series Earth and Environmental Science, 37 (012039). pp. 1-11. ISSN 1755-1307; ESSN: 1755-1315 10.1088/1755-1315/37/1/012039
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description To increase the quality of palm oil means to accurately grade the oil palm fresh fruit bunches (FFB) for processing. In this paper, HSI color model was used to determine the relationship between FFB ' s color with the underipe and ripe category so that the grading system could be accurately done. From the analysis manipulation, a formula was generated and applied to the data obtained. The by linear regression in the data shows an average success rate at 45% accuracy for oil palm ripeness detection. Artificial Neural Network (ANN) however return a better accuracy result for both underipe and ripe categories which are 60% and 80% respectively. This yield an overall accuracy of 70%. This can be increased more by improving the grading system.
format Article
author Shabdin, Muhammad Kashfi
Mohamed Shariff, Abdul Rashid
Johari, Mohd Nazrul Azlan
Saat, Nor Kamilah
Abbas, Zulkifly
spellingShingle Shabdin, Muhammad Kashfi
Mohamed Shariff, Abdul Rashid
Johari, Mohd Nazrul Azlan
Saat, Nor Kamilah
Abbas, Zulkifly
A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
author_facet Shabdin, Muhammad Kashfi
Mohamed Shariff, Abdul Rashid
Johari, Mohd Nazrul Azlan
Saat, Nor Kamilah
Abbas, Zulkifly
author_sort Shabdin, Muhammad Kashfi
title A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
title_short A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
title_full A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
title_fullStr A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
title_full_unstemmed A study on the oil palm fresh fruit bunch (FFB) ripeness detection by using Hue, Saturation and Intensity (HSI) approach
title_sort study on the oil palm fresh fruit bunch (ffb) ripeness detection by using hue, saturation and intensity (hsi) approach
publisher IOP Publishing
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/54942/1/A%20study%20on%20the%20oil%20palm%20fresh%20fruit%20bunch%20%28FFB%29%20ripeness%20detection%20by%20using%20Hue%2C%20Saturation%20and%20Intensity%20%28HSI%29%20approach.pdf
http://psasir.upm.edu.my/id/eprint/54942/
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score 13.211869

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