Deep Face Recognition For Surveillance And Access Control

Abstract

The most important domain of research field in biometric technology is facial recognition and its applications are widely utilized for security purposes to consumer applications, monitoring solutions to industrial efficiency, access control and surveillance etc. Most of the existing facial recognition systems are based on old techniques which give poor accuracy and vulnerable to lightning and other environmental conditions. To address these problems, we propose a Deep Face Recognition system for surveillance, access control and other security purposes. We also focus on making a smart attendance system in which attendance can be marked by the faces of people appearing in the camera. In this project, we prepare custom dataset for facial recognition. We perform data augmentation to increase the variation and size of custom datasets. We utilize pre-trained VGG-16 model for deep face recognition. We fine-tune the VGG-16 model with our custom dataset and trained it. We implement our project for access control, surveillance, and facial attendance. In access control setup, if the person is not recognized by our system, the access to the gate will be denied. We also maintain a database of people appearing in front of the camera during access control setup. We record the time of entry, name of person and the image of the person in our database for surveillance and record purpose. In facial attendance setup, our system provides the ease to mark the attendance of all the registered persons appearing in front of the camera and their names and time of attendance will be stored in the database. Our system also provides the facility of registration of new persons in the existing record. We made an efficient graphical user interface to provide all the abovementioned facilities. We also implemented our complete project on an embedded platform raspberry pi 4 to shape our project in form of a portable product.