Facial Recognition-Based Attendance Management System

Abstract

In today's educational and professional environments, the accurate and secure tracking of attendance is crucial, demanding systems that are efficient, adaptable, and punctual. This project proposes an innovative solution to this pressing challenge by leveraging facial recognition technology, specifically methods like LBPH (Local Binary Patterns Histogram) and Haar cascade, to introduce a robust "Facial Recognition Based Attendance Management System." This system represents a significant advancement in attendance monitoring, offering a user-friendly and dependable solution suitable for schools and businesses alike. The rapid evolution of biometric technologies, including techniques such as LBPH and Haar cascade, has revolutionized attendance monitoring and management for institutions and enterprises. Among various biometric approaches, facial recognition, employing algorithms like LBPH and Haar cascade, has emerged as a promising and non-intrusive method for achieving precise attendance tracking.In our comprehensive survey paper, we conduct an in-depth examination of the current state-of-the-art facial recognition-based attendance management systems, particularly those utilizing LBPH and Haar cascade algorithms. Our analysis explores multiple aspects of these systems, including underlying technologies, implementation challenges, advantages, and ethical considerations. This thorough investigation provides a wellrounded perspective on this rapidly evolving field.