A characterization of watermelon leaf diseases using Fuzzy Logic

A characterization of watermelon leaf diseases using Fuzzy Logic

This paper presents a characterization of watermelon leaf diseases through the RGB color. The aim of this study is to perform identification of selected critical watermelon leaf diseases in Malaysia namely the Downy Mildew and Anthracnose diseases. Several samples of infected leaves images were put...

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Published in:ISBEIA 2012 - IEEE Symposium on Business, Engineering and Industrial Applications
Main Author: 2-s2.0-84874375469
Format: Conference paper
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874375469&doi=10.1109%2fISBEIA.2012.6422869&partnerID=40&md5=8ad3b60f5b57de4e1db0fc2fba51010c
id Abdullah N.E.; Hashim H.; Yusof Y.W.M.; Osman F.N.; Kusim A.S.; Adam M.S.
spelling Abdullah N.E.; Hashim H.; Yusof Y.W.M.; Osman F.N.; Kusim A.S.; Adam M.S.
2-s2.0-84874375469
A characterization of watermelon leaf diseases using Fuzzy Logic
2012
ISBEIA 2012 - IEEE Symposium on Business, Engineering and Industrial Applications


10.1109/ISBEIA.2012.6422869
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874375469&doi=10.1109%2fISBEIA.2012.6422869&partnerID=40&md5=8ad3b60f5b57de4e1db0fc2fba51010c
This paper presents a characterization of watermelon leaf diseases through the RGB color. The aim of this study is to perform identification of selected critical watermelon leaf diseases in Malaysia namely the Downy Mildew and Anthracnose diseases. Several samples of infected leaves images were put under digital RGB color extraction where the images were captured under standardized and controlled environment. This study involves 200 samples of infected leaves of which the classification of the diseases was carried out using Fuzzy Logic technique. Fuzzy Logic was used to handle the uncertainty and vagueness as it provides a means of translating qualitative and imprecise information into quantitative (linguistic) terms. The results have shown that the percentage of accuracy for both types of disease were more than 67%. Copyright © 2012 IEEE.


English
Conference paper
author 2-s2.0-84874375469
spellingShingle 2-s2.0-84874375469
A characterization of watermelon leaf diseases using Fuzzy Logic
author_facet 2-s2.0-84874375469
author_sort 2-s2.0-84874375469
title A characterization of watermelon leaf diseases using Fuzzy Logic
title_short A characterization of watermelon leaf diseases using Fuzzy Logic
title_full A characterization of watermelon leaf diseases using Fuzzy Logic
title_fullStr A characterization of watermelon leaf diseases using Fuzzy Logic
title_full_unstemmed A characterization of watermelon leaf diseases using Fuzzy Logic
title_sort A characterization of watermelon leaf diseases using Fuzzy Logic
publishDate 2012
container_title ISBEIA 2012 - IEEE Symposium on Business, Engineering and Industrial Applications
container_volume
container_issue
doi_str_mv 10.1109/ISBEIA.2012.6422869
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874375469&doi=10.1109%2fISBEIA.2012.6422869&partnerID=40&md5=8ad3b60f5b57de4e1db0fc2fba51010c
description This paper presents a characterization of watermelon leaf diseases through the RGB color. The aim of this study is to perform identification of selected critical watermelon leaf diseases in Malaysia namely the Downy Mildew and Anthracnose diseases. Several samples of infected leaves images were put under digital RGB color extraction where the images were captured under standardized and controlled environment. This study involves 200 samples of infected leaves of which the classification of the diseases was carried out using Fuzzy Logic technique. Fuzzy Logic was used to handle the uncertainty and vagueness as it provides a means of translating qualitative and imprecise information into quantitative (linguistic) terms. The results have shown that the percentage of accuracy for both types of disease were more than 67%. Copyright © 2012 IEEE.
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issn
language English
format Conference paper
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