A survey on machine learning-based facial recognition algorithm

A Method of perceiving a human face through innovation is cleared by face recognition. Face identification and recognition have been utilized in the security frameworks, access control which has acquired sufficient ubiquity over the most recent couple of years. Biometrics is utilized to plan facial highlights from a photo or video in a facial recognition framework. A database of known faces is used to compare the information to find a match. Facial recognition can verify personal identity, but it also raises privacy issues. This paper compares the different facial recognition algorithms and reviews them. We aim to come up with an approach that best suits a database and gives high accuracy. This paper intends to focus on different face recognition methods and gives a brief view of the application. It also gives a comparative study of various parameters for the measurement of the performance of an algorithm for a particular database system, Yale Database, and ORL Database. The comparative study on different approaches depicts each algorithm’s performance and its limitations.