Problem statement
Traditional access control systems often rely on manual methods or card-based
systems, which can be prone to security breaches, unauthorized access, and
inconvenience. Improving security and user experience in controlled environments
remains a challenge
Abstract
The Facial Recognition-based Access Control System project aims to enhance security
and user convenience by implementing a biometric access control system. Utilizing
facial recognition technology, the system will allow or deny access based on the unique
facial features of authorized individuals, providing a more secure and seamless entry
process.
Outcome
The outcome of this project is a sophisticated access control system that enhances
security through biometric authentication. The facial recognition technology ensures
accurate identification, reducing the risk of unauthorized access. The system offers a
user-friendly experience, eliminating the need for physical access cards or PINs.
Overall, it contributes to a more robust and efficient access control paradigm in various
environments.
Reference
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.
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https://ieeexplore.ieee.org/document/9263894