AUTOMATED ATTENDANCE SYSTEM USING FACE RECOGNITION
Keywords:
Attendance System, Face Recognition,, Automated Process, Manual Process,, OpenCV, Student Information,, Roll Number, Photographs, Time Management, Classroom Device,, Dataset Training, Modernization, Automation.Abstract
Attendance management is a vital daily activity in educational institutions,
workplaces, and organizations, traditionally carried out using manual methods such as
roll calls or name-based identification. These conventional approaches are time-
intensive, prone to human error, and inefficient, especially in large groups. This
project proposes an automated attendance system that leverages face recognition
technology to address these challenges and modernize the process. The system is
designed to be installed in classrooms or similar environments, where it captures and
processes the facial data of individuals for attendance tracking. Students' information,
including their name, roll number, class, section, and facial images, is pre-registered
and stored in a structured dataset. Using the OpenCV library, the system extracts,
processes, and trains the facial images to create a robust recognition model. Before
the start of a class, students interact with the system, which scans their faces, matches
the captured data with the stored dataset, and automatically records attendance upon
successful identification. By eliminating the need for manual intervention, the system
enhances accuracy, saves time, and ensures a seamless and efficient attendance
process. Furthermore, it aligns with the growing need for digital transformation by
introducing a secure, user-friendly, and technologically advanced solution that
improves operational efficiency and minimizes errors.
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