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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2014
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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 |
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QA76 Computer software Ahmad, Faudziah Airuddin, Ahmad Categories leaf healthiness using RGB spectrum and fuzzy logic |
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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 |
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2014 |
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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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1644281526956851200 |
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13.209306 |