Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch

Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested at the optimum stage for maximum oil production. Current harvesting methods based on observing the number of loose fruits on ground and the color of the fruits using hum...

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Main Author:	Fadilah, Norasyikin
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK1-9971 Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.usm.my/61135/1/24%20Pages%20from%2000001785141.pdf
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id	my-usm-ep.61135
record_format	uketd_dc
spelling	my-usm-ep.611352024-09-18T01:40:28Z Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch 2015-01 Fadilah, Norasyikin TK1-9971 Electrical engineering. Electronics. Nuclear engineering Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested at the optimum stage for maximum oil production. Current harvesting methods based on observing the number of loose fruits on ground and the color of the fruits using human vision lead to subjective evaluation, laborious work, and low quality oil. Therefore, this research focuses on the development of an automated system with the ability to process the image of oil palm FFB and determine its ripeness category. The system consists of an image acquisition system, image processing component and oil palm FFB classification system. Images of oil palm FFBs of type DxP Yangambi are acquired using an IP camera which is attached to the end of a pole and connected to a computer via the RJ45 cable. The images are collected and analyzed using digital image processing techniques. k-means clustering algorithm is used to segment the image into two separate regions which are fruit and spike regions. Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm. 2015-01 Thesis http://eprints.usm.my/61135/ http://eprints.usm.my/61135/1/24%20Pages%20from%2000001785141.pdf application/pdf en public masters Perpustakaan Hamzah Sendut Pusat Pengajian Kejuruteraan Elektrik & Elektronik
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	TK1-9971 Electrical engineering Electronics Nuclear engineering
spellingShingle	TK1-9971 Electrical engineering Electronics Nuclear engineering Fadilah, Norasyikin Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
description	Ripeness classification of oil palm fresh fruit bunches (FFBs) during harvesting is important to ensure that they are harvested at the optimum stage for maximum oil production. Current harvesting methods based on observing the number of loose fruits on ground and the color of the fruits using human vision lead to subjective evaluation, laborious work, and low quality oil. Therefore, this research focuses on the development of an automated system with the ability to process the image of oil palm FFB and determine its ripeness category. The system consists of an image acquisition system, image processing component and oil palm FFB classification system. Images of oil palm FFBs of type DxP Yangambi are acquired using an IP camera which is attached to the end of a pole and connected to a computer via the RJ45 cable. The images are collected and analyzed using digital image processing techniques. k-means clustering algorithm is used to segment the image into two separate regions which are fruit and spike regions. Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm.
format	Thesis
qualification_level	Master's degree
author	Fadilah, Norasyikin
author_facet	Fadilah, Norasyikin
author_sort	Fadilah, Norasyikin
title	Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
title_short	Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
title_full	Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
title_fullStr	Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
title_full_unstemmed	Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
title_sort	intelligent color vision system for ripeness classification of oil palm fresh fruit bunch
granting_institution	Perpustakaan Hamzah Sendut
granting_department	Pusat Pengajian Kejuruteraan Elektrik & Elektronik
publishDate	2015
url	http://eprints.usm.my/61135/1/24%20Pages%20from%2000001785141.pdf
_version_	1811772883509182464

Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch

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