Facial Anthropometry-Based Masked Face Recognition System

Okokpujie, Kennedy O. and Okokpujie, Imhade P. and Abioye, Fortress Abigail and Subair, Roselyn E. and Akingunsoye, Adenugba Vincent (2024) Facial Anthropometry-Based Masked Face Recognition System. Ingénierie des Systèmes d’Information, 29 (3). pp. 809-820.

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Abstract

Different kinds of occlusion have proven to disrupt the accuracy of face recognition systems, one of them being masks. The problem of masked faces has become even more apparent with the widespread of the COVID-19 virus, with most people wearing masks in public. This brings up the issue of existing face recognition systems been able to accurately recognize people even when part of their face and the major identifiers (such as the nose and mouth) are covered by a facemask. In addition, most of the databases that have been curated in different organizations, countries are majorly of non-masked faces, and masked databases are rarely stored or universally accepted compared with conventional face datasets. Therefore, this paper aim at the development of a Masked Face Recognition System using facial anthropometrics technique (FAT). FAT is the science of calculating the measurements, proportion and dimension of human face and their features. A dataset of faces with individual wearing medical face mask was curated. Using the Facial anthropometry based technique a Masked Face Recognition System developed. This system was implemented using Local Binary Patterns Histogram algorithms for recognition. On testing the developed system trained with unmasked dataset, show a high recognition performance of 94% and 96.8% for masked and non-masked face recognition respectively because of the Facial anthropometry based technique adapted. On deployment, users were been recognized when they are wearing a mask with part of their face covered in real-time.

Item Type:	Article
Uncontrolled Keywords:	masked face recognition, unmasked face recognition, facial Anthropometry, COVID- 19, facemask, facial landmarks, Local Binary Pattern Histogram, biometric, craniofacial plexus, face size, facial index, intercanthal index, orbital width index, nasal index
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	nwokealisi
Date Deposited:	29 Nov 2024 09:01
Last Modified:	29 Nov 2024 09:01
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/18626

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