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Real time visual system for starfruit maturity index classification

Considering the demand for fresh starfruit becomes higher nowadays, an automatic system for starfruit quality inspection is mostly needed since the quality inspection of starfruit is still manually performed by human. The objectives of this thesis are to develop a real time visual system and to impl...

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Main Author: Amirulah, Rahman
Format: Thesis
Language:English
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/36556/1/RahmanAmirulahMFKE2012.pdf
http://eprints.utm.my/id/eprint/36556/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:69750?site_name=Restricted Repository
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spelling my.utm.365562017-09-25T05:36:36Z http://eprints.utm.my/id/eprint/36556/ Real time visual system for starfruit maturity index classification Amirulah, Rahman TK Electrical engineering. Electronics Nuclear engineering Considering the demand for fresh starfruit becomes higher nowadays, an automatic system for starfruit quality inspection is mostly needed since the quality inspection of starfruit is still manually performed by human. The objectives of this thesis are to develop a real time visual system and to implement the colour maturity algorithm into a Field Programmable Gates Array (FPGA) system for starfruit colour maturity classification. Generally, the system designed in this work consists of three main sub-systems: input, process and output. The input of the system is acquired by using a digital camera with YCbCr format. The second part of the system is the main processing system which is FPGA. The processes on the FPGA can be divided into three parts, which are segmentation, feature extraction and classification. The segmentation process is utilised to determine the Region Of Interest (ROI) of the starfruit area by using fixed threshold value based on Cb component. The feature fed to the system is extracted from Cr component that becomes the input to the proposed rule-based classifier. In this work, the starfruit is classified into 6 maturity levels. The performance of the proposed system achieved 89% of starfruit correctly classified. 2012-10 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/36556/1/RahmanAmirulahMFKE2012.pdf Amirulah, Rahman (2012) Real time visual system for starfruit maturity index classification. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:69750?site_name=Restricted Repository
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Amirulah, Rahman
Real time visual system for starfruit maturity index classification
description Considering the demand for fresh starfruit becomes higher nowadays, an automatic system for starfruit quality inspection is mostly needed since the quality inspection of starfruit is still manually performed by human. The objectives of this thesis are to develop a real time visual system and to implement the colour maturity algorithm into a Field Programmable Gates Array (FPGA) system for starfruit colour maturity classification. Generally, the system designed in this work consists of three main sub-systems: input, process and output. The input of the system is acquired by using a digital camera with YCbCr format. The second part of the system is the main processing system which is FPGA. The processes on the FPGA can be divided into three parts, which are segmentation, feature extraction and classification. The segmentation process is utilised to determine the Region Of Interest (ROI) of the starfruit area by using fixed threshold value based on Cb component. The feature fed to the system is extracted from Cr component that becomes the input to the proposed rule-based classifier. In this work, the starfruit is classified into 6 maturity levels. The performance of the proposed system achieved 89% of starfruit correctly classified.
format Thesis
author Amirulah, Rahman
author_facet Amirulah, Rahman
author_sort Amirulah, Rahman
title Real time visual system for starfruit maturity index classification
title_short Real time visual system for starfruit maturity index classification
title_full Real time visual system for starfruit maturity index classification
title_fullStr Real time visual system for starfruit maturity index classification
title_full_unstemmed Real time visual system for starfruit maturity index classification
title_sort real time visual system for starfruit maturity index classification
publishDate 2012
url http://eprints.utm.my/id/eprint/36556/1/RahmanAmirulahMFKE2012.pdf
http://eprints.utm.my/id/eprint/36556/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:69750?site_name=Restricted Repository
_version_ 1643649980159754240
score 13.211869

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