Oil Palm Fruit Bunches Grading System

Grading of oil palm fruit bunches manually may subjected to mistake and human error while examining the right category of the fruit bunches for the purpose of oil palm production in the oil palm mill. Hence, it is important to identify and classify the quality of the oil palm . fruit bunches. Image...

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Main Author: Sim, Shiang Wei
Format: Final Year Project Report
Language:English
English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2015
Subjects:
Online Access:http://ir.unimas.my/id/eprint/38953/1/SIM%20SHIANG%20WEI%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/38953/4/SIM%20SHIANG%20WEI%20%28fulltext%29.pdf
http://ir.unimas.my/id/eprint/38953/
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spelling my.unimas.ir.389532024-01-31T08:52:17Z http://ir.unimas.my/id/eprint/38953/ Oil Palm Fruit Bunches Grading System Sim, Shiang Wei Q Science (General) QA76 Computer software Grading of oil palm fruit bunches manually may subjected to mistake and human error while examining the right category of the fruit bunches for the purpose of oil palm production in the oil palm mill. Hence, it is important to identify and classify the quality of the oil palm . fruit bunches. Image processing technique is implemented into the oil palm fruit bunches grading system. The grading system developed manage to distinguish between the four different categories of oil palm fruit bunches which are including unripe, under ripe, ripe and over ripe. The methodology consists of six stages which are including image acquisition, image pre-processing, color processing, image segmentation, classification, and results and evaluation. The saturation element in the HSV model was selected as the parameter for the threshold value. The ripeness of the oil palm fruit bunch could be differentiated between the different categories of fruit bunches based on the percentage of the ripeness areas masked on the surface of the fruit. The fruit classification ability of the prototype system yields above 85% accuracy from the experiment results achieved. By implementing the image processing technique into the grading system can help to increase the efficiency and quality of grading the fruit bunches for oil palm mill. Universiti Malaysia Sarawak, (UNIMAS) 2015 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/38953/1/SIM%20SHIANG%20WEI%20%2824%20pgs%29.pdf text en http://ir.unimas.my/id/eprint/38953/4/SIM%20SHIANG%20WEI%20%28fulltext%29.pdf Sim, Shiang Wei (2015) Oil Palm Fruit Bunches Grading System. [Final Year Project Report] (Unpublished)
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
English
topic Q Science (General)
QA76 Computer software
spellingShingle Q Science (General)
QA76 Computer software
Sim, Shiang Wei
Oil Palm Fruit Bunches Grading System
description Grading of oil palm fruit bunches manually may subjected to mistake and human error while examining the right category of the fruit bunches for the purpose of oil palm production in the oil palm mill. Hence, it is important to identify and classify the quality of the oil palm . fruit bunches. Image processing technique is implemented into the oil palm fruit bunches grading system. The grading system developed manage to distinguish between the four different categories of oil palm fruit bunches which are including unripe, under ripe, ripe and over ripe. The methodology consists of six stages which are including image acquisition, image pre-processing, color processing, image segmentation, classification, and results and evaluation. The saturation element in the HSV model was selected as the parameter for the threshold value. The ripeness of the oil palm fruit bunch could be differentiated between the different categories of fruit bunches based on the percentage of the ripeness areas masked on the surface of the fruit. The fruit classification ability of the prototype system yields above 85% accuracy from the experiment results achieved. By implementing the image processing technique into the grading system can help to increase the efficiency and quality of grading the fruit bunches for oil palm mill.
format Final Year Project Report
author Sim, Shiang Wei
author_facet Sim, Shiang Wei
author_sort Sim, Shiang Wei
title Oil Palm Fruit Bunches Grading System
title_short Oil Palm Fruit Bunches Grading System
title_full Oil Palm Fruit Bunches Grading System
title_fullStr Oil Palm Fruit Bunches Grading System
title_full_unstemmed Oil Palm Fruit Bunches Grading System
title_sort oil palm fruit bunches grading system
publisher Universiti Malaysia Sarawak, (UNIMAS)
publishDate 2015
url http://ir.unimas.my/id/eprint/38953/1/SIM%20SHIANG%20WEI%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/38953/4/SIM%20SHIANG%20WEI%20%28fulltext%29.pdf
http://ir.unimas.my/id/eprint/38953/
_version_ 1789945489531076608
score 13.160551