Novel Feature Extraction for Oil Palm Bunches Classification

Wang, Hui Hui and Wang, Yin Chai and Wee, Bui Lin and Sim, Shiang Wei (2024) Novel Feature Extraction for Oil Palm Bunches Classification. Journal of Advanced Research in Applied Sciences and Engineering Technology, 34 (1). pp. 350-360. ISSN 2462-1943

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Abstract

This paper presents research on an image processing approach for oil palm fruit brunches classification on automating the process of classifying palm fruit brunches based on their visual characteristics, which can have applications in the agriculture and palm oil industry. The research aims to classify the bunches into four categories which are unripe, under ripe, ripe and over ripe. Additionally, this approach can reduce the manual labour involved in palm oil grading and provide a more objective and consistent method for grading the oil. The proposed approach consists of the process of image acquisition, image pre-processing, colour processing, image segmentation and classification. The ripeness of the oil palm fruit bunches is determined based on the percentage of ripeness areas masked on the fruit surface. The proposed algorithms successfully classified the palm oil bunches and improved the accuracy of grading palm oil, achieving 85% accuracy from the experiment results

Item Type: Article
Uncontrolled Keywords: Palm Oil Classification; Image Processing; Ripeness; Feature Extraction.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 19 Mar 2024 01:36
Last Modified: 19 Mar 2024 01:36
URI: http://ir.unimas.my/id/eprint/44468

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