Generative AI-Based Real-Time Face Aging Simulation for Biometric Systems

¹ Department of Information Science Engineering, New Horizon College of Engineering, Bangalore, India.
² Lovely Professional University, Phagwara, India.
³ Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, Telangana, India.
⁴ Lloyd Law College, Plot No. 11, Knowledge Park II, Greater Noida, Uttar Pradesh, 201308, India.
⁵ Hilla University College, Babylon, Iraq
⁶ Department of Electrical and Electronics Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, India

^* Corresponding Author: rjanandhi@hotmail.com

Abstract

Facial recognition is, therefore, a crucial aspect of biometric systems used when authenticating as well as verifying people’s identity. But here natural aging increases a number of difficulties concerning accuracy and long-term reliability of the control systems stated above. In this paper, a new method of real-time face aging simulation in the context of aging variance of biometric systems using Generative AI; specifically, GANs, is proposed. The proposed model tries to use generative AI in generation of improved synthetics with modified age appearance, allowing biometric systems to capture aging or antiaging changes in facial features. This approach is assessed experimentally from one facial database to another datasets and the principal area of interest is the future recognition accuracy of faces in the long run with respect to age groups. This work also looks at the strength and robustness of the model for real-time problems. The outcomes presented here show that applying generative AI-based system as a paradigm improves the performance of the biometric system specifically for addressing aging variations thus proposing a valuable solution to age- related biometric problems. The paper also considers some possible consequences for security, privacy, and concerns to practical application in real systems.