A facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.

With recent advancements in deep learning, face recognition has become highly accurate, with accuracy levels of over 99% with confidence thresholds of false acceptance rate of one in one thousand.

There are 2 components to the Facial Recognition Technology

Facial Detection :- the software component that detects if a face(s) is present in the image. A face detection system uses machine learning or deep learning algorithms to determine the presence and location of faces in a still image or video frame. The process is anonymous – face detection is not used to identify the detected face or faces. It also does not store any personally identifiable information. It merely places a bounding box around the faces that it detects to show where in the image or video those faces are situated

Facial Recognition :- the software component that maps, analyzes, and then confirms the identity of a face in a photograph or video. A face recognition system works by taking an image of a face and making a prediction about whether the face matches another face or other faces in a provided database. The technology is designed to compare and predict potential matches of faces regardless of their expression, facial hair, and age.