Access Control System Based on Face Recognition

Face recognition is a technology that uses face image of someone to verify his identity by finding this person in a given photos database. It becomes very practical in access control systems as it does not require any physical interaction for gaining access as traditional ways with keys. Moreover, these systems only require a camera for recognition and are easy to install and use. This is why they are already in use by companies as access control to their offices, in home automation systems, etc.In this paper, different approaches to face recognition are studied. The first step of any face recognition system is face detection and cropping so we analyzed classical Viola-Jones face detection and MultiTask Convolutional Neural Networks (MTCNN) in terms of detection quality and processing time.The final classifier obtained is capable of matching face from the online camera to image from a given database. We also considered decreasing the vulnerability of standalone face recognition by adding a spoof detection method so that the system does not react to every approach to bypass the system like showing a photo of an allowed person shown on a phone's screen.