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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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science (IAES)
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/18514/ http://umpir.ump.edu.my/id/eprint/18514/1/7528-7674-1-PB.pdf |
| _version_ | 1848820690546851840 |
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| 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. |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T02:13:28Z |
| format | Article |
| id | ump-18514 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:13:28Z |
| publishDate | 2017 |
| publisher | Institute of Advanced Engineering and Science (IAES) |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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. (Published) http://iaesjournal.com/online/index.php/IJECE/article/view/15194 DOI: 10.11591/ijece.v7i3.pp1594-1601 |
| 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 |
| title | 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_short | Face Recognition Using Completed Local Ternary Pattern (CLTP) Texture Descriptor |
| title_sort | face recognition using completed local ternary pattern (cltp) texture descriptor |
| topic | QA75 Electronic computers. Computer science |
| 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 |