Class Attendance Monitoring System Using Face Recognition

R. Thanmayi , Mrs. D. Anusha , A. Charan Teja , G. Nitish Mouli , V. Varun Raju

Face Recognition, Attendance marking, OpenCV, Flask, K-Nearest Neighbors.

Marking attendance in a classroom during a session is not only a tedious task but also a time consuming one. The presence of abnormally large number of students during the session leads to high chances of proxy attendance. Marking presence with conventional methods has been a complicated task. The increased demand in efficient and automatic techniques of marking attendance is a problematic aspect in the area of face recognition. Earlier, the issue of automatic attendance marking has been managed through standard biometrics like fingerprint, RFID, Iris Biometric, etc. Anyway, these techniques lack reliability. This paper endeavours to design an automated system that records the attendance with the usage of facial recognition. The system allows the user to post name, Id and images while adding a new student data and stores the images based on the coordinates of the face location in the database. A facial recognition model is trained based on the dataset of images. It initializes a K-Nearest Neighbors classifier with a specified number of neighbors and fits the model on the known faces and names. After training the model, attendance can be marked along with the time of registered students in an excel sheet which can be viewed and downloaded.

Published Paper   E-Certificate

"Class Attendance Monitoring System Using Face Recognition", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e330-e335, March-2023, Available :https://ijnrd.org/papers/IJNRD2303444.pdf

Volume 8 Issue 3, March-2023

Pages : e330-e335

Paper Reg. ID: IJNRD_189885

Published Paper Id: IJNRD2303444

Downloads: 000118844

Research Area: Engineering

Country: VISHAKHAPATNAM, ANDHRA PRADESH, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303444

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303444

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition