Multi-Angle Facial Recognition: Enhancing Biometric Security with a Broadly Positioned Stereo-Camera System

Haq, Muhamad Amirul and Huy, Le Nam Quoc and Ridlwan, Muhammad and Naila, Ishmatun (2024) Multi-Angle Facial Recognition: Enhancing Biometric Security with a Broadly Positioned Stereo-Camera System. E3S Web of Conferences, 500. ISSN 2267-1242

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Abstract

This study addresses the vulnerabilities of traditional monocular camera-based face recognition systems, emphasizing the need for improved security and reliability in biometric authentication under varying environmental conditions, lighting, and human poses. To counteract the risk of spoofing attacks using masks or static images, we introduce a multi-angle stereo camera system. This system is strategically designed to capture facial imagery from multiple perspectives, thereby enhancing depth perception and spatial accuracy, crucial for high-security authentication. Employing a novel image processing approach, the study integrates a Convolutional Neural Networks (CNN) with a simple Boolean operation to differentiate the landmarks detected on each camera. This method exploits CNN’s robust feature extraction capabilities and the effective usage of stereo camera, enabling precise detection and analysis of 3D facial landmarks. Such an approach significantly bolsters the system’s ability to differentiate between genuine faces and deceptive representations like masks or static images. Empirical results demonstrate that the stereo camera configuration substantially improves recognition accuracy, reducing both false positives and negatives, especially in controlled spoofing scenarios. The advanced 3D facial landmark detection further reinforces the system’s security. With its enhanced robustness and security, the developed system shows great potential for applications in areas requiring stringent identity verification, such as banking, public facilities, and smart home technologies.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Artikel Website > Fakultas Teknik
Depositing User:	Muhamad Amirul Haq
Date Deposited:	18 Mar 2024 01:52
Last Modified:	18 Mar 2024 01:52
URI:	http://repository.um-surabaya.ac.id/id/eprint/9163

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