A Review of Face Recognization Technology

DOI

10.2991/978-94-6463-718-2_115How to use a DOI?

Keywords

face recognition; privacy-preserving techniques; federated learning; algorithm accuracy; bias reduction; security features

Abstract

The face recognition technology has evolved and tackled many challenges while also providing opportunities for enhancement in diverse domains. Concerns regarding the privacy of the training data have given rise to privacy-preserving methodologies, including federated learning and least effort protection via encryption, to encourage responsible adoption. The improved performance of these systems is due to continuous improvements in algorithmic accuracy that have resulted in robust systems that can solve problems in the real world like changing lighting conditions, pose changes, and occlusion. After October 2023, there has been a heightened scrutiny to minimize gender and racial bias and the face recognition systems are now more equitable and inclusive. In addition, improved security features have made these systems less vulnerable to spoofing and adversarial attacks. Overcoming real time processing challenges has led to greater computational resources optimization, cloud solutions and edge computing adoption, all of which demand more efficient and scalable systems. Facial recognition systems became more robust to environment conditions, i.e., they were more resilient to changing real-world environments. Legal and regulatory progress demands more in terms of clear ethical parameters and protection of data, creating more transparency and fostering accountability. As such, ethical concerns underpin the uptake of human rights-based technologies, and integration issues are catalysing the development of standardised interoperable systems. Due to falling implementation costs, face recognition is becoming increasingly popular, with adoption cutting across multiple sectors, including security, healthcare, and customer service.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - B. Rajesh
AU  - R. Vijhayalakshme
AU  - R. Ramesh
AU  - B. Raghul
AU  - P. Vimal Raj
AU  - V. Monisha
PY  - 2025
DA  - 2025/05/23
TI  - A Review of Face Recognization Technology
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1381
EP  - 1395
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_115
DO  - 10.2991/978-94-6463-718-2_115
ID  - Rajesh2025
ER  -