Categories leaf healthiness using RGB spectrum and fuzzy logic

In this paper, a general approach is to classify of the green leaf healthiness.Fuzzy logic tool (FuzzyLite 3.2 software) and color features (RGB Spectrum) are used in this experiment.Mean values of primary colors (Red, Green and Blue) channels as input to FIS (Fuzzy Inference System).FIS gives dec...

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Main Authors: Ahmad, Faudziah, Airuddin, Ahmad
Format: Conference or Workshop Item
Language:English
Published: 2014
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Online Access:http://repo.uum.edu.my/14707/1/K22.pdf
http://repo.uum.edu.my/14707/
http://www.kmice.cms.net.my/kmice2014/intro.asp
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spelling my.uum.repo.147072016-04-27T07:23:03Z http://repo.uum.edu.my/14707/ Categories leaf healthiness using RGB spectrum and fuzzy logic Ahmad, Faudziah Airuddin, Ahmad QA76 Computer software In this paper, a general approach is to classify of the green leaf healthiness.Fuzzy logic tool (FuzzyLite 3.2 software) and color features (RGB Spectrum) are used in this experiment.Mean values of primary colors (Red, Green and Blue) channels as input to FIS (Fuzzy Inference System).FIS gives decision whether this part of leaf is healthy, unhealthy or dying.Experimentation is conducted on our own dataset for determining knowledge base, consisting of 40 images of leaves for each category; 20 for training and 20 for testing.The experiment has 4 phases which were data preparation, features extraction, features selection and classification.The experimental results indicate that proposed model achieves a good average classification accuracy which are 85% healthy,95% unhealthy and 100% dying. 2014-08-12 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/14707/1/K22.pdf Ahmad, Faudziah and Airuddin, Ahmad (2014) Categories leaf healthiness using RGB spectrum and fuzzy logic. In: Knowledge Management International Conference 2014 (KMICe2014), 12-15 August 2014, Langkawi, Malaysia. http://www.kmice.cms.net.my/kmice2014/intro.asp
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Ahmad, Faudziah
Airuddin, Ahmad
Categories leaf healthiness using RGB spectrum and fuzzy logic
description In this paper, a general approach is to classify of the green leaf healthiness.Fuzzy logic tool (FuzzyLite 3.2 software) and color features (RGB Spectrum) are used in this experiment.Mean values of primary colors (Red, Green and Blue) channels as input to FIS (Fuzzy Inference System).FIS gives decision whether this part of leaf is healthy, unhealthy or dying.Experimentation is conducted on our own dataset for determining knowledge base, consisting of 40 images of leaves for each category; 20 for training and 20 for testing.The experiment has 4 phases which were data preparation, features extraction, features selection and classification.The experimental results indicate that proposed model achieves a good average classification accuracy which are 85% healthy,95% unhealthy and 100% dying.
format Conference or Workshop Item
author Ahmad, Faudziah
Airuddin, Ahmad
author_facet Ahmad, Faudziah
Airuddin, Ahmad
author_sort Ahmad, Faudziah
title Categories leaf healthiness using RGB spectrum and fuzzy logic
title_short Categories leaf healthiness using RGB spectrum and fuzzy logic
title_full Categories leaf healthiness using RGB spectrum and fuzzy logic
title_fullStr Categories leaf healthiness using RGB spectrum and fuzzy logic
title_full_unstemmed Categories leaf healthiness using RGB spectrum and fuzzy logic
title_sort categories leaf healthiness using rgb spectrum and fuzzy logic
publishDate 2014
url http://repo.uum.edu.my/14707/1/K22.pdf
http://repo.uum.edu.my/14707/
http://www.kmice.cms.net.my/kmice2014/intro.asp
_version_ 1644281526956851200
score 13.209306