A picture of ripeness: investigating image-based techniques for oil palm fruit grading
Oil palm is a highly efficient crop that can produce more oil per unit of land than any other type of oil seed. Palm oil it is in high demand, and its production can significantly contribute to a country’s economic growth. However, the traditional method of grading palm fruit is still prevalent in M...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Malaysian Palm Oil Board
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/116761/ http://psasir.upm.edu.my/id/eprint/116761/1/116761.pdf |
| _version_ | 1848867085302628352 |
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| author | Rosbi, Munirah Omar, Zaid Hanafi, Marsyita |
| author_facet | Rosbi, Munirah Omar, Zaid Hanafi, Marsyita |
| author_sort | Rosbi, Munirah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Oil palm is a highly efficient crop that can produce more oil per unit of land than any other type of oil seed. Palm oil it is in high demand, and its production can significantly contribute to a country’s economic growth. However, the traditional method of grading palm fruit is still prevalent in Malaysia, which requires skilled workers to classify the harvested fruit according to its ripeness. This approach can be costly and labour-intensive. Therefore, several studies have investigated automated palm fruit classification techniques that could reduce costs and labour in the industry. This paper provides a review of these studies, with a specific focus on vision-based classification techniques. The article discusses approaches based on image processing encompassing pre-processing, feature extraction and classification steps. The survey’s results indicate that there is a lack of technique to effectively address outdoor images, such as colour correction methods. Therefore, further research is necessary to develop a better segmentation and colour correction procedures. Overall, the findings of this study could help improve the efficiency and sustainability of palm oil production, thereby contributing to economic growth and environmental conservation. |
| first_indexed | 2025-11-15T14:30:53Z |
| format | Article |
| id | upm-116761 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:30:53Z |
| publishDate | 2024 |
| publisher | Malaysian Palm Oil Board |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1167612025-04-15T07:58:26Z http://psasir.upm.edu.my/id/eprint/116761/ A picture of ripeness: investigating image-based techniques for oil palm fruit grading Rosbi, Munirah Omar, Zaid Hanafi, Marsyita Oil palm is a highly efficient crop that can produce more oil per unit of land than any other type of oil seed. Palm oil it is in high demand, and its production can significantly contribute to a country’s economic growth. However, the traditional method of grading palm fruit is still prevalent in Malaysia, which requires skilled workers to classify the harvested fruit according to its ripeness. This approach can be costly and labour-intensive. Therefore, several studies have investigated automated palm fruit classification techniques that could reduce costs and labour in the industry. This paper provides a review of these studies, with a specific focus on vision-based classification techniques. The article discusses approaches based on image processing encompassing pre-processing, feature extraction and classification steps. The survey’s results indicate that there is a lack of technique to effectively address outdoor images, such as colour correction methods. Therefore, further research is necessary to develop a better segmentation and colour correction procedures. Overall, the findings of this study could help improve the efficiency and sustainability of palm oil production, thereby contributing to economic growth and environmental conservation. Malaysian Palm Oil Board 2024-02-14 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/116761/1/116761.pdf Rosbi, Munirah and Omar, Zaid and Hanafi, Marsyita (2024) A picture of ripeness: investigating image-based techniques for oil palm fruit grading. Journal of Oil Palm Research, 37 (1). pp. 1-15. ISSN 2811-4701 https://jopr.mpob.gov.my/a-picture-of-ripeness-investigating-image-based-techniques-for-oil-palm-fruit-grading/ 10.21894/jopr.2024.0015 |
| spellingShingle | Rosbi, Munirah Omar, Zaid Hanafi, Marsyita A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title | A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title_full | A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title_fullStr | A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title_full_unstemmed | A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title_short | A picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| title_sort | picture of ripeness: investigating image-based techniques for oil palm fruit grading |
| url | http://psasir.upm.edu.my/id/eprint/116761/ http://psasir.upm.edu.my/id/eprint/116761/ http://psasir.upm.edu.my/id/eprint/116761/ http://psasir.upm.edu.my/id/eprint/116761/1/116761.pdf |