Face Recognition System for Medical Information Modeling Using Machine Learning

Abstract

Face-recognition systems must be capable of identifying patient faces in an uncontrollable situation. Facial detection is a distinct problem from facial recognition in that it needs to report the location and size of all of the faces in a given image, which is not possible with face recognition. There are numerous changes in the images of the same face, which makes it a difficult problem to solve because of their general likeness in appearance. Face recognition is a very difficult procedure to do in an uncontrolled environment, since the lighting and angle of the face, as well as the quality of the image to be recognized, all have a considerable influence on the outcome of the process. This chapter provides information regarding the various face recognition machine learning models. The performance of the models is compared on the basis of values derived for FAR, FRR, TSR, and ERR.