Face recognition using laplacian completed local ternary pattern (LapCLTP)

Nowadays, the face is one of the typical biometrics that has high-security technology in the biometrics field. In face recognition systems, feature extraction is considered as one of the important steps. In feature extraction, the important and interesting parts of the image are represented as a com...

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Main Authors: Sam, Yin Yee, Rassem, Taha Hussein, Mohammed, Mohammed Falah, Suryanti, Awang
Format: Conference or Workshop Item
Language:English
Published: Springer 2020
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/28449/
http://umpir.ump.edu.my/id/eprint/28449/7/Face%20recognition%20using%20laplacian%20completed%20local%20ternary%20pattern%20.pdf
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author Sam, Yin Yee
Rassem, Taha Hussein
Mohammed, Mohammed Falah
Suryanti, Awang
author_facet Sam, Yin Yee
Rassem, Taha Hussein
Mohammed, Mohammed Falah
Suryanti, Awang
author_sort Sam, Yin Yee
building UMP Institutional Repository
collection Online Access
description Nowadays, the face is one of the typical biometrics that has high-security technology in the biometrics field. In face recognition systems, feature extraction is considered as one of the important steps. In feature extraction, the important and interesting parts of the image are represented as a compact feature vector. Many features had been proposed in the image processing fields such as texture, colour, and shape. Recently, texture descriptors are playing an important and significant role as a local descriptor. Different types of texture descriptors had been proposed and used for face recognition task, such as Local Binary Pattern (LBP), Local Ternary Pattern (LTP), and Completed Local Ternary Pattern (CLTP). All these texture features have achieved good performances in terms of recognition accuracy. In this paper, we propose to improve the performance of the CLTP and use it for face recognition. A Laplacian Completed Local Ternary Pattern (LapCLTP) is proposed in this paper. The image is enhanced using a Laplacian filter for pre-processing image process before extracting the CLTP. JAFFR and YALE standard face datasets are used to investigate the performance of the LapCLTP. The experiment results showed that the LapCLTP outperformed the original CLTP in both datasets and achieved higher recognition accuracy. The LapCLTP achieved 99.24%, while CLTP achieved 98.78% with JAFFE dataset. IN YALE, the LapCLTP achieved 85.13%, while CLTP, only 84.46%.
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format Conference or Workshop Item
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institution Universiti Malaysia Pahang
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language English
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spelling ump-284492024-01-08T01:18:13Z http://umpir.ump.edu.my/id/eprint/28449/ Face recognition using laplacian completed local ternary pattern (LapCLTP) Sam, Yin Yee Rassem, Taha Hussein Mohammed, Mohammed Falah Suryanti, Awang QA75 Electronic computers. Computer science QA76 Computer software Nowadays, the face is one of the typical biometrics that has high-security technology in the biometrics field. In face recognition systems, feature extraction is considered as one of the important steps. In feature extraction, the important and interesting parts of the image are represented as a compact feature vector. Many features had been proposed in the image processing fields such as texture, colour, and shape. Recently, texture descriptors are playing an important and significant role as a local descriptor. Different types of texture descriptors had been proposed and used for face recognition task, such as Local Binary Pattern (LBP), Local Ternary Pattern (LTP), and Completed Local Ternary Pattern (CLTP). All these texture features have achieved good performances in terms of recognition accuracy. In this paper, we propose to improve the performance of the CLTP and use it for face recognition. A Laplacian Completed Local Ternary Pattern (LapCLTP) is proposed in this paper. The image is enhanced using a Laplacian filter for pre-processing image process before extracting the CLTP. JAFFR and YALE standard face datasets are used to investigate the performance of the LapCLTP. The experiment results showed that the LapCLTP outperformed the original CLTP in both datasets and achieved higher recognition accuracy. The LapCLTP achieved 99.24%, while CLTP achieved 98.78% with JAFFE dataset. IN YALE, the LapCLTP achieved 85.13%, while CLTP, only 84.46%. Springer 2020 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/28449/7/Face%20recognition%20using%20laplacian%20completed%20local%20ternary%20pattern%20.pdf Sam, Yin Yee and Rassem, Taha Hussein and Mohammed, Mohammed Falah and Suryanti, Awang (2020) Face recognition using laplacian completed local ternary pattern (LapCLTP). In: Advances in Electronics Engineering: Proceedings of the ICCEE 2019 , 29-30 April 2019 , Kuala Lumpur, Malaysia. pp. 315-327., 619. ISBN 978-981-15-1289-6 (Published) https://doi.org/10.1007/978-981-15-1289-6_29 https://doi.org/10.1007/978-981-15-1289-6_29
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Sam, Yin Yee
Rassem, Taha Hussein
Mohammed, Mohammed Falah
Suryanti, Awang
Face recognition using laplacian completed local ternary pattern (LapCLTP)
title Face recognition using laplacian completed local ternary pattern (LapCLTP)
title_full Face recognition using laplacian completed local ternary pattern (LapCLTP)
title_fullStr Face recognition using laplacian completed local ternary pattern (LapCLTP)
title_full_unstemmed Face recognition using laplacian completed local ternary pattern (LapCLTP)
title_short Face recognition using laplacian completed local ternary pattern (LapCLTP)
title_sort face recognition using laplacian completed local ternary pattern (lapcltp)
topic QA75 Electronic computers. Computer science
QA76 Computer software
url http://umpir.ump.edu.my/id/eprint/28449/
http://umpir.ump.edu.my/id/eprint/28449/
http://umpir.ump.edu.my/id/eprint/28449/
http://umpir.ump.edu.my/id/eprint/28449/7/Face%20recognition%20using%20laplacian%20completed%20local%20ternary%20pattern%20.pdf