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Classification Of Wood Defect Images Using Local Binary Pattern Variants

This paper presents an analysis of the statistical texture representation of the Local Binary Pattern (LBP) variants in the classification of wood defect images. The basic and variants of the LBP feature set that was constructed from a stage of feature extraction processes with the Basic LBP, Rotati...

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Main Authors: Rahiddin, Rahillda Nadhirah Norizzaty, Hashim, Ummi Rabaah, Ismail, Nor Haslinda, Salahuddin, Lizawati, Ngo, Hea Choon, Zabri@Suhaimi, Siti Normi
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2020
Online Access:http://eprints.utem.edu.my/id/eprint/25004/2/2020%2C%20UMMI%2C%20CLASSIFICATION_OF_WOOD_DEFECT_IMAGES.PDF
http://eprints.utem.edu.my/id/eprint/25004/
http://ijain.org/index.php/IJAIN/article/view/392/ijain_v6i1_p36-45
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spelling my.utem.eprints.250042021-04-20T11:48:52Z http://eprints.utem.edu.my/id/eprint/25004/ Classification Of Wood Defect Images Using Local Binary Pattern Variants Rahiddin, Rahillda Nadhirah Norizzaty Hashim, Ummi Rabaah Ismail, Nor Haslinda Salahuddin, Lizawati Ngo, Hea Choon Zabri@Suhaimi, Siti Normi This paper presents an analysis of the statistical texture representation of the Local Binary Pattern (LBP) variants in the classification of wood defect images. The basic and variants of the LBP feature set that was constructed from a stage of feature extraction processes with the Basic LBP, Rotation Invariant LBP, Uniform LBP, and Rotation Invariant Uniform LBP. For significantly discriminating, the wood defect classes were further evaluated with the use of different classifiers. By comparing the results of the classification performances that had been conducted across the multiple wood species, the Uniform LBP was found to have demonstrated the highest accuracy level in the classification of the wood defects. Universitas Ahmad Dahlan 2020-03 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25004/2/2020%2C%20UMMI%2C%20CLASSIFICATION_OF_WOOD_DEFECT_IMAGES.PDF Rahiddin, Rahillda Nadhirah Norizzaty and Hashim, Ummi Rabaah and Ismail, Nor Haslinda and Salahuddin, Lizawati and Ngo, Hea Choon and Zabri@Suhaimi, Siti Normi (2020) Classification Of Wood Defect Images Using Local Binary Pattern Variants. International Journal of Advances in Intelligent Informatics, 6 (1). pp. 36-45. ISSN 2442-6571 http://ijain.org/index.php/IJAIN/article/view/392/ijain_v6i1_p36-45 10.26555/ijain.v6i1.392
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
description This paper presents an analysis of the statistical texture representation of the Local Binary Pattern (LBP) variants in the classification of wood defect images. The basic and variants of the LBP feature set that was constructed from a stage of feature extraction processes with the Basic LBP, Rotation Invariant LBP, Uniform LBP, and Rotation Invariant Uniform LBP. For significantly discriminating, the wood defect classes were further evaluated with the use of different classifiers. By comparing the results of the classification performances that had been conducted across the multiple wood species, the Uniform LBP was found to have demonstrated the highest accuracy level in the classification of the wood defects.
format Article
author Rahiddin, Rahillda Nadhirah Norizzaty
Hashim, Ummi Rabaah
Ismail, Nor Haslinda
Salahuddin, Lizawati
Ngo, Hea Choon
Zabri@Suhaimi, Siti Normi
spellingShingle Rahiddin, Rahillda Nadhirah Norizzaty
Hashim, Ummi Rabaah
Ismail, Nor Haslinda
Salahuddin, Lizawati
Ngo, Hea Choon
Zabri@Suhaimi, Siti Normi
Classification Of Wood Defect Images Using Local Binary Pattern Variants
author_facet Rahiddin, Rahillda Nadhirah Norizzaty
Hashim, Ummi Rabaah
Ismail, Nor Haslinda
Salahuddin, Lizawati
Ngo, Hea Choon
Zabri@Suhaimi, Siti Normi
author_sort Rahiddin, Rahillda Nadhirah Norizzaty
title Classification Of Wood Defect Images Using Local Binary Pattern Variants
title_short Classification Of Wood Defect Images Using Local Binary Pattern Variants
title_full Classification Of Wood Defect Images Using Local Binary Pattern Variants
title_fullStr Classification Of Wood Defect Images Using Local Binary Pattern Variants
title_full_unstemmed Classification Of Wood Defect Images Using Local Binary Pattern Variants
title_sort classification of wood defect images using local binary pattern variants
publisher Universitas Ahmad Dahlan
publishDate 2020
url http://eprints.utem.edu.my/id/eprint/25004/2/2020%2C%20UMMI%2C%20CLASSIFICATION_OF_WOOD_DEFECT_IMAGES.PDF
http://eprints.utem.edu.my/id/eprint/25004/
http://ijain.org/index.php/IJAIN/article/view/392/ijain_v6i1_p36-45
_version_ 1698700617524969472
score 13.211869

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