In-Depth Analysis and Research on Facial Recognition Technology

Abstract

Facial recognition is a biometric identification technology based on computer vision. It captures facial images through cameras, extracts key features like the nose, ears, and eyes, then converts them into comparable digital data in order to identity verification. This technology is widely used in smartphone unlocking, access control systems, payment authentication, and public security tracking, offering advantages such as eliminating the need for physical cards or memorized passwords while providing fast and efficient verification.However, current challenges include reduced accuracy due to poor lighting conditions or angle variations, as well as security risks like privacy breaches and data misuse. As facial recognition technology continues to evolve, enhancing user privacy and data security has become increasingly urgent, even as the technology improves societal convenience.Through extensive research, this study analyzes and summarizes the technical characteristics and development trends of traditional methods (PCA) and modern approaches (CNN) in facial recognition. The findings aim to work as a reference for recent studies and future applications and study,also providing a foundation for expanding research perspectives and clarifying future development directions.