ATTENDANCE SYSTEM USING FACE RECOGNITION TECHNIQUES

ATTENDANCE SYSTEM USING FACE RECOGNITION TECHNIQUES

Monisha D M, Devayush A, J Yashas, Madhura B S, Nabard Biju Sharma

Department of Computer Science and Engineering, Presidency University, Bangalore, India

Abstract

If attendance is managed by hand, it might be a significant strain for the teachers. A clever and automated attendance management system is being used to overcome this problem. However, in this system, authentication is a critical concern. Biometrics are commonly used to implement smart attendance systems. One of the biometric approaches for improving this system is face recognition. Facial recognition, as a key aspect of biometric verification, is widely employed in a variety of applications, including video surveillance and CCTV systems, computer-human interaction, indoor access systems, and network security. The problem of proxies and students being marked present even when they are not physically there can be easily solved with this architecture. Face detection and recognition are the two most important implementation steps in this type of system. Using Eigen face values, Principle Component Analysis (PCA), and Convolutional Neural Networks, this study provides a model for constructing an automated attendance management system for students in a class (CNN). Following that, a link of recognized faces should be possible by comparing them to a database of student faces. This strategy will be a successful method of managing student attendance and records.

Keywords: Python, Face Detection, Face Extraction, Face Recognition, Attendance Marking