Abstract:

The development of a face recognition-based attendance monitoring system for educational institutions is the main objective of this automated attendance management system based on facial recognition. This will update and improve the current attendance system to make it more effective and efficient than it was before. The current, out-of-date system is highly unclear, which leads to inaccurate and inefficient attendance tracking.When the authority cannot enforce the regulations that are in place under the current system, many issues arise. To make it possible to recognize each student's face specifically, this project was created. The face recognition system will be the technology at work. One of the natural characteristics that can be used to distinguish an individual is their face. Because it is unlikely for a face to differ or be replicated, it is utilized to trace identification. In this project, data will be fed into the recognizer algorithm through the creation of image folders. Next, during the session for recording attendance, the folder containing the sought-after identify will be compared to the faces. The attendance will be automatically recorded when a person is recognized, entering the necessary information into an excel sheet. At the end of the day, the appropriate faculty members receive an email including the excel sheet containing each person's attendance information. By introducing a faculty module next to the student module, we are modernizing it to make it more functional, and the attendance records will be displayed immediately on the main page.

Description:

Face Recognition, Attendance Management System, LBPH Algorithm, Open CV, Cascading file, Tkinter interface