Smart Attendance Management System Using Face Recognition

Abstract

Traditional attendance systems are time-consuming and prone to errors such as proxy attendance, duplicate entries, and manual data handling issues. This paper presents a Smart Attendance Management System using Face Recognition Technology developed with Python programming language. The proposed system automates attendance marking using computer vision and machine learning techniques. The system uses OpenCV and the Local Binary Pattern Histogram (LBPH) algorithm for face detection and recognition. Attendance records are stored securely in a MySQL database and exported automatically into Excel reports. An additional email notification feature is integrated to send attendance reports automatically to registered email addresses.

Introduction

The text presents a Smart Attendance Management System designed to replace traditional manual and biometric attendance methods, which are often slow, error-prone, and vulnerable to proxy attendance. The proposed system uses facial recognition technology implemented with Python, OpenCV, and the LBPH (Local Binary Pattern Histogram) algorithm to automatically identify individuals and mark attendance.

Attendance data is securely stored in a MySQL database and can be exported as Excel reports. The system also includes an email notification feature to automatically send attendance summaries.

The methodology involves user registration, image preprocessing, face detection, feature extraction using LBPH, face recognition, attendance marking, report generation, and email notifications. The system architecture integrates image capture, processing, database management, and reporting modules.

Experimental results show that the system successfully recognizes faces in real time and records attendance automatically.

Conclusion

The Smart Attendance Management System using Face Recognition Technology provides an efficient and automated solution for attendance management. The proposed system reduces manual effort, improves attendance accuracy, and provides secure contactless attendance management.

References

[1] OpenCV Documentation, https://opencv.org/ [2] Python Software Foundation, https://www.python.org/ [3] MySQL Documentation, https://www.mysql.com/ [4] Ahonen T., Hadid A., Pietikainen M., “Face Recognition with Local Binary Patterns,” IEEE, 2006. [5] R. Gonzalez and R. Woods, “Digital Image Processing,” Pearson Education, 2018.

Copyright

Copyright © 2026 Ayesha Fathima, Mohammed Yaser, Prakruthi S S, Dhanya T S. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.