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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2016
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| 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 |
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| author | Shabdin, Muhammad Kashfi Mohamed Shariff, Abdul Rashid Johari, Mohd Nazrul Azlan Saat, Nor Kamilah Abbas, Zulkifly |
| author_facet | Shabdin, Muhammad Kashfi Mohamed Shariff, Abdul Rashid Johari, Mohd Nazrul Azlan Saat, Nor Kamilah Abbas, Zulkifly |
| author_sort | Shabdin, Muhammad Kashfi |
| collection | UPM |
| 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. |
| first_indexed | 2024-03-06T09:22:01Z |
| format | Article |
| id | upm.eprints-54942 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:22:01Z |
| publishDate | 2016 |
| publisher | IOP Publishing |
| record_format | dspace |
| spelling | 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 |
| 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 |
| title | 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_short | 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 |
| 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 |
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