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Volume 150
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Proceeding Paper

Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control †

by
Fatima Sapundzhi
1,*,
Ramazan Ertuğrul Aydoğan
1,
Slavi Georgiev
2,3,* and
Nikita Nikitov
2
1
Department of Communication and Computer Engineering, Faculty of Engineering, South-West University “Neofit Rilski”, 66 Ivan Myhailov Str., 2700 Blagoevgrad, Bulgaria
2
Department of Applied Mathematics and Statistics, Faculty of Natural Sciences and Education, University of Ruse, 8 Studentska Str., 7004 Ruse, Bulgaria
3
Department of Information Modeling, Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Acad. G. Bonchev Str. Bl. 8, 1113 Sofia, Bulgaria
*
Authors to whom correspondence should be addressed.
†
Presented at the 15th International Scientific Conference TechSys 2026—Engineering, Technologies and Systems, Plovdiv, Bulgaria, 14–16 May 2026.
Eng. Proc. 2026, 150(1), 11; https://doi.org/10.3390/engproc2026150011
Published: 17 July 2026
(This article belongs to the Proceedings of The 15th International Scientific Conference TechSys 2026—Engineering, Technologies and Systems)
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Abstract

The current study presents the design, implementation, and evaluation of a real-time face recognition system for automated access control. The system uses Python libraries to build an accurate and secure identification platform that incorporates dedicated stages for facial data processing and recognition. During data preparation, 128-dimensional facial embedding vectors are generated for authorized users through a command-line interface and protected using authenticated encryption. In real-time operation, the system captures video frames, detects faces, and verifies identities by matching them against the encrypted database. Experimental results demonstrate high recognition accuracy, real-time throughput, and robust performance, highlighting the system’s suitability for GDPR-oriented deployment in small institutional environments.
Keywords: face recognition; access control; computer vision; real-time systems; facial embeddings; biometrics; privacy; GDPR face recognition; access control; computer vision; real-time systems; facial embeddings; biometrics; privacy; GDPR

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MDPI and ACS Style

Sapundzhi, F.; Aydoğan, R.E.; Georgiev, S.; Nikitov, N. Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control. Eng. Proc. 2026, 150, 11. https://doi.org/10.3390/engproc2026150011

AMA Style

Sapundzhi F, Aydoğan RE, Georgiev S, Nikitov N. Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control. Engineering Proceedings. 2026; 150(1):11. https://doi.org/10.3390/engproc2026150011

Chicago/Turabian Style

Sapundzhi, Fatima, Ramazan Ertuğrul Aydoğan, Slavi Georgiev, and Nikita Nikitov. 2026. "Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control" Engineering Proceedings 150, no. 1: 11. https://doi.org/10.3390/engproc2026150011

APA Style

Sapundzhi, F., Aydoğan, R. E., Georgiev, S., & Nikitov, N. (2026). Architecture and Performance Evaluation of Real-Time Facial Recognition for Access Control. Engineering Proceedings, 150(1), 11. https://doi.org/10.3390/engproc2026150011

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