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Computer programs that can recognize, track, identify, or validate human faces in pictures or videos are known as face recognition programs(Yang & Han, 2020a) .This biometric security system recognizes a person by their face traits.(Yang & Han, 2020). People can be recognized in images, films, or in real time using facial recognition technology. Systems for recognizing faces employ distinct mathematical patterns to store biometric information. They are among the safest and most reliable identifying techniques available in biometric technology as a result(Grudin, 2000). To lower the possibility of unwanted access, facial data can be privatized and anonymized. The technique of recognizing or verifying a person's identification using technology based on images, videos, or in-the-moment surveillance of their face is known as facial recognition.(Kortli et al., 2020) . Facial recognition systems may generally be utilized for two kinds of tasks: identification and verification. The background of facial recognition technology. Woody Bledsoe, Helen Chan Wolf, and Charles Bisson were the pioneers of automated facial recognition in the 1960s, with their work centered on teaching computers to recognize human faces. In addition to lowering crime rates, enhancing safety and security, and minimizing human contact, facial recognition technology has benefits for society(Annual IEEE Computer Conference et al., n.d.). The following are a few benefits of facial recognition: aids in the recovery of missing persons. Safeguards companies from theft. It varies according to the kind of facial recognition we're discussing(Yang & Han, 2020b). Among the safest in the business is Apple's 3D facial recognition system. However, 2D facial recognition, which is present in the majority of phones, is not very safe. Its lack of security implies that it won't open for someone else's face, but it might still open for a photographer, while you're asleep, or when you wear makeup or sunglasses and it can't identify your presence(Zhang & Institute of Electrical and Electronics Engineers, n.d.). It will be simpler for the recognition system to discover and identify faces in clear, well-focused photographs with decent illumination. Encourage your subjects to keep their postures and facial expressions consistent when the camera is focused on them. This can improve the system's ability to match faces between various photos. Crucial elements encompass the separation between your eyes, the profundity of your eye sockets, the arc from your forehead to your chin, the form of your cheekbones, and the outline of your lips, ears, and chin(Phillips et al., 2005). Finding the facial landmarks that are essential to differentiating your face is the goal. Low image quality or inadequate lighting can affect facial recognition systems(Lu et al., n.d.). Because of obstructed camera angles, the data might not match the person's nodal points; this results in an error when matching faceprints cannot be confirmed in the database.