A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features

Recently, many approaches have been introduced by several researchers to identify plants. Now, applications of texture, shape, color and vein features are common practices. However, there are many possibilities of methods can be developed to improve the performance of such identification systems....

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Main Author: Kadir, Abdul
Format: Article
Language:English
Published: 2014
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/11803/1/A_Model_of_Plant_Identification_System_Using_GLCM%2C_Lacunarity_and_Shen.pdf
http://eprints.utem.edu.my/id/eprint/11803/
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spelling my.utem.eprints.118032015-05-28T04:20:22Z http://eprints.utem.edu.my/id/eprint/11803/ A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features Kadir, Abdul T Technology (General) SB Plant culture Recently, many approaches have been introduced by several researchers to identify plants. Now, applications of texture, shape, color and vein features are common practices. However, there are many possibilities of methods can be developed to improve the performance of such identification systems. Therefore, several experiments had been conducted in this research. As a result, a new novel approach by using combination of Gray-Level Co-occurrence Matrix, lacunarity and Shen features and a Bayesian classifier gives a better result compared to other plant identification systems. For comparison, this research used two kinds of several datasets that were usually used for testing the performance of each plant identification system. The results show that the system gives an accuracy rate of 97.19% when using the Flavia dataset and 95.00% when using the Foliage dataset and outperforms other approaches. 2014-03 Article PeerReviewed application/pdf en cc_by_nc http://eprints.utem.edu.my/id/eprint/11803/1/A_Model_of_Plant_Identification_System_Using_GLCM%2C_Lacunarity_and_Shen.pdf Kadir, Abdul (2014) A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 5 (2). pp. 1-10. ISSN 0975-8585
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
SB Plant culture
spellingShingle T Technology (General)
SB Plant culture
Kadir, Abdul
A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
description Recently, many approaches have been introduced by several researchers to identify plants. Now, applications of texture, shape, color and vein features are common practices. However, there are many possibilities of methods can be developed to improve the performance of such identification systems. Therefore, several experiments had been conducted in this research. As a result, a new novel approach by using combination of Gray-Level Co-occurrence Matrix, lacunarity and Shen features and a Bayesian classifier gives a better result compared to other plant identification systems. For comparison, this research used two kinds of several datasets that were usually used for testing the performance of each plant identification system. The results show that the system gives an accuracy rate of 97.19% when using the Flavia dataset and 95.00% when using the Foliage dataset and outperforms other approaches.
format Article
author Kadir, Abdul
author_facet Kadir, Abdul
author_sort Kadir, Abdul
title A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
title_short A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
title_full A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
title_fullStr A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
title_full_unstemmed A Model of Plant Identification System Using GLCM, Lacunarity and Shen Features
title_sort model of plant identification system using glcm, lacunarity and shen features
publishDate 2014
url http://eprints.utem.edu.my/id/eprint/11803/1/A_Model_of_Plant_Identification_System_Using_GLCM%2C_Lacunarity_and_Shen.pdf
http://eprints.utem.edu.my/id/eprint/11803/
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score 13.209306