Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor

Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recogn...

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Main Authors:	Rassem, Taha H., Makbol, Nasrin M., Sam, Yin Yee
Format:	Article
Language:	English
Published:	Institute of Advanced Engineering and Science (IAES) 2017
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/1/7528-7674-1-PB.pdf

id	ump-18514
recordtype	eprints
spelling	ump-185142018-03-20T04:22:20Z http://umpir.ump.edu.my/id/eprint/18514/ Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor Rassem, Taha H. Makbol, Nasrin M. Sam, Yin Yee QA75 Electronic computers. Computer science Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recognition accuracy. Local binary pattern (LBP) and many of its variants used as texture features in many of face recognition systems. Although LBP performed well in many fields, it is sensitive to noise, and different patterns of LBP may classify into the same class that reduces its discriminating property. Completed Local Ternary Pattern (CLTP) is one of the new proposed texture features to overcome the drawbacks of the LBP. The CLTP outperformed LBP and some of its variants in many fields such as texture, scene, and event image classification. In this study, we study and investigate the performance of CLTP operator for face recognition task. The Japanese Female Facial Expression (JAFFE), and FEI face databases are used in the experiments. In the experimental results, CLTP outperformed some previous texture descriptors and achieves higher classification rate for face recognition task which has reached up 99.38% and 85.22% in JAFFE and FEI, respectively. Institute of Advanced Engineering and Science (IAES) 2017-06 Article PeerReviewed application/pdf en cc_by_nc_nd http://umpir.ump.edu.my/id/eprint/18514/1/7528-7674-1-PB.pdf Rassem, Taha H. and Makbol, Nasrin M. and Sam, Yin Yee (2017) Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor. International Journal of Electrical and Computer Engineering (IJECE), 7 (3). pp. 1594-1601. ISSN 2088-8708 http://iaesjournal.com/online/index.php/IJECE/article/view/15194 DOI: 10.11591/ijece.v7i3.pp1594-1601
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Rassem, Taha H. Makbol, Nasrin M. Sam, Yin Yee Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
description	Nowadays, face recognition becomes one of the important topics in the computer vision and image processing area. This is due to its importance where can be used in many applications. The main key in the face recognition is how to extract distinguishable features from the image to perform high recognition accuracy. Local binary pattern (LBP) and many of its variants used as texture features in many of face recognition systems. Although LBP performed well in many fields, it is sensitive to noise, and different patterns of LBP may classify into the same class that reduces its discriminating property. Completed Local Ternary Pattern (CLTP) is one of the new proposed texture features to overcome the drawbacks of the LBP. The CLTP outperformed LBP and some of its variants in many fields such as texture, scene, and event image classification. In this study, we study and investigate the performance of CLTP operator for face recognition task. The Japanese Female Facial Expression (JAFFE), and FEI face databases are used in the experiments. In the experimental results, CLTP outperformed some previous texture descriptors and achieves higher classification rate for face recognition task which has reached up 99.38% and 85.22% in JAFFE and FEI, respectively.
format	Article
author	Rassem, Taha H. Makbol, Nasrin M. Sam, Yin Yee
author_facet	Rassem, Taha H. Makbol, Nasrin M. Sam, Yin Yee
author_sort	Rassem, Taha H.
title	Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
title_short	Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
title_full	Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
title_fullStr	Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
title_full_unstemmed	Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor
title_sort	face recognition using completed local ternary pattern (cltp) texture descriptor
publisher	Institute of Advanced Engineering and Science (IAES)
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/1/7528-7674-1-PB.pdf
first_indexed	2023-09-18T22:26:16Z
last_indexed	2023-09-18T22:26:16Z
_version_	1777415986815696896

Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor

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