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Abstract

The face recognition system is a biometric technique that replaces traditional passwords and personal identification. This research is dedicated to presenting a study of some facial recognition systems. Since it is unlikely to replicate and is more stable over time, the domain of facial feature extraction has proven to be more effective in attaining exact facial recognition, which is important, especially in intelligent security surveillance systems. Face recognition systems encounter several challenges, primarily related to pose variations, illumination conditions, and occlusions such as hair, glasses, and so on. To address these challenges, enhance performance, and boost the accuracy and speed of identification, a wide range of mechanisms were developed to carry out the face recognition function, which converts the face image into a digital feature that allows for effective comparison and storage. This survey highlights more than 25 face recognition systems. The review analyzed the systems based on performance metrics, classifier efficiency, and feature extraction techniques, as well as their strengths, weaknesses, and suitability for real-time applications. It also described the most popular databases used to test the performance of face recognition systems. Additionally, recommendations for future research directions in face recognition have been offered.

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