Automated access control system using face recognition. (2021)

• Record Type: Journal Article
• Authors: Rameswari, R.; Naveen Kumar, S.; Abishek Aananth, M.; Deepak, C.
• Is Part Of: Materials today. Volume 45:Part 2(2021)
• Page Start: 1251
• Page End: 1256
• Publication Date: 2021
• Subjects: Computer vision -- Face detection -- Face recognition -- FaceNet -- Histogram Object Gradient -- Webpage; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.04.664
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: Security to every firm or campus is an essential one nowadays, as the crime rates in recent days are increasing day by day. As the world is transforming into an advanced technological trend, automated systems are implemented in many sectors. Here in this sector, it will be much more effective. Thus many automated access control systems are being implemented such as biometric methods and fingerprint-based access systems. But these existing systems undergo many complications that lead to time consumption in long. Thus face recognition based access systems are introduced which provides us the better solution. There are many face recognition access systems with different algorithms. This paper deals with an effective and modern algorithm called the FaceNet algorithm. The access system with this algorithm uses Face encoding to detect the face and eye which works effectively on light/illumination changes. Later on the facial feature extraction is done by using the Histogram Object Gradient (HOG). Compare face function, which contains Support Vector Machine classifier to classify the face encoding and produces the output. RFID sensor and IR sensor is implemented to make the system function effectively. Also in addition a webpage is created to provide the access authority to the management of the campus or firm where they can also handle the access system manually if needed.