Face recognition using laplacian completed local ternary pattern (LapCLTP)

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

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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%.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Face recognition; Completed local ternary pattern (CLTP); Laplacian filter; (LAPCLTP); Image classification; Face database
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Dr. Taha Hussein Alaaldeen Rassem
Date Deposited: 13 Jul 2020 03:26
Last Modified: 08 Jan 2024 01:18
URI: http://umpir.ump.edu.my/id/eprint/28449
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