Attendance management system using Python (Haar cascade and Open-CV)
S. Maurya, Bhavneet Kaur, P. Rawat · IET conference proceedings. · 2023
The Attendance Management System using Haar cascade and OpenCV is a Python-based project that aims to automate the process of attendance management in various settings such as schools, colleges, or workplaces. The system utilizes computer vision techniques, specifically Haar cascade and OpenCV, to detect and recognize faces from images or video streams, enabling accurate and efficient attendance tracking. Traditional methods of attendance management involve manual processes, such as taking roll calls or signing attendance sheets, which can be time-consuming, prone to errors, and inefficient. Automating the attendance management process using computer vision techniques can significantly streamline the process, eliminate manual errors, and save time and resources. The conventional methods of attendance management often suffer from challenges such as inaccuracies, buddy punching (where one person marks attendance for another), and time-consuming administrative tasks. These issues can lead to discrepancies in attendance records and create difficulties in maintaining accurate attendance data.