Face Detection and Recognition System

Abstract

Face detection and recognition are among the most commonly used technologies in our daily lives. The technology has been used in many personal and commercial applications, like surveillance, security, healthcare, advertising and safety. This project aims at designing and developing a software for face detection and recognition systems with a promising detection and recognition performance rate. The system has the ability to: run on a real captured input from a digital camera, take appropriate actions and, finally, alert the system admin when a captured face is not recognised in the database or any other outcome, depending on the purpose of the face detection system. In the case of an unrecognised face, the system alerts the admin using a pop-up message displaying that the user is not recognised. The implementation of the system takes about four seconds to process each captured face image. This is because the system implements and extends the capabilities of both the Viola and Jones method and Principal Component Analysis. The implementation is also carried out on Python 2 due to its high performance, stability and huge support community.