An Extensive Study on Traditional-to-Recent Transformation on Face Recognition System

Abstract

The face is the most visible biometric feature considered in manual and automated systems to identify individuals. In recent years, the inventions of low-cost high-resolution mobile cameras and surveillance systems have increased the usage and popularity of facial recognition systems. Today, various mobile apps, ICT systems, electronic devices, and cloud-based systems are using facial verification to gain access and authorization based security. Now, the facial recognition system has become a generalized authentication system instead of a specialized capability of specialized applications. This increasing scope and applications are reflected as the challenges and criticalities that exist in the real environment. The technological transformation was investigated by the researchers in image types, facial capturing, facial rectification, feature generation, and classification methods and techniques of face recognition systems. This paper has provided an extensive study on each stage of standard FRS (Face Recognition System). The methods and measures provided by researchers for improving and optimizing face normalization, segmentation, feature generation, and face recognition are provided in this paper. Each of the methods is also defined along with the performance, accuracy, and robustness against various addressed challenges. The paper has provided a map between the traditional and recent methods to explore the advancement in facial verification systems.