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A new method for fruits recognition system

Several fruit recognition techniques are developed based upon color and shape attributes. However, different fruit images may have similar or identical color and shape values. Hence, using color features and shape features analysis methods are still not robust and effective enough to identify and di...

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Main Authors: Seng, W.C., Mirisaee, S.H.
Format: Conference or Workshop Item
Published: 2009
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.um.edu.my/2300/
http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=2&SID=V1NBDfJepe1pIfMKN6P&page=20&doc=191&cacheurlFromRightClick=no
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spelling my.um.eprints.23002014-12-29T07:01:02Z http://eprints.um.edu.my/2300/ A new method for fruits recognition system Seng, W.C. Mirisaee, S.H. QA75 Electronic computers. Computer science Several fruit recognition techniques are developed based upon color and shape attributes. However, different fruit images may have similar or identical color and shape values. Hence, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruits images. A new fruit recognition system has been proposed, which combines three features analysis methods: color-based, shape-based and size-based in order to increase accuracy of recognition. The proposed method classifies and recognizes fruit images based on obtained feature values by using nearest neighbours; classification. Consequently, our system shows the fruit name and a short description to user. The proposed fruit recognition system analysis classifies and identifies fruits successfully up to 90% accuracy. This system also serves as a useful tool in a variety of fields such as education, image retrieval and plantation science. 2009 Conference or Workshop Item PeerReviewed Seng, W.C. and Mirisaee, S.H. (2009) A new method for fruits recognition system. In: International Conference on Electrical Engineering and Informatics, AUG 05-07, 2009 , Bangi, MALAYSIA. http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=2&SID=V1NBDfJepe1pIfMKN6P&page=20&doc=191&cacheurlFromRightClick=no
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Seng, W.C.
Mirisaee, S.H.
A new method for fruits recognition system
description Several fruit recognition techniques are developed based upon color and shape attributes. However, different fruit images may have similar or identical color and shape values. Hence, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruits images. A new fruit recognition system has been proposed, which combines three features analysis methods: color-based, shape-based and size-based in order to increase accuracy of recognition. The proposed method classifies and recognizes fruit images based on obtained feature values by using nearest neighbours; classification. Consequently, our system shows the fruit name and a short description to user. The proposed fruit recognition system analysis classifies and identifies fruits successfully up to 90% accuracy. This system also serves as a useful tool in a variety of fields such as education, image retrieval and plantation science.
format Conference or Workshop Item
author Seng, W.C.
Mirisaee, S.H.
author_facet Seng, W.C.
Mirisaee, S.H.
author_sort Seng, W.C.
title A new method for fruits recognition system
title_short A new method for fruits recognition system
title_full A new method for fruits recognition system
title_fullStr A new method for fruits recognition system
title_full_unstemmed A new method for fruits recognition system
title_sort new method for fruits recognition system
publishDate 2009
url http://eprints.um.edu.my/2300/
http://apps.webofknowledge.com/full_record.do?product=UA&search_mode=Refine&qid=2&SID=V1NBDfJepe1pIfMKN6P&page=20&doc=191&cacheurlFromRightClick=no
_version_ 1643686896118792192
score 13.211869

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