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Face Recognition Attendance System

Prachi Goel1 , Abdul Aleem Ansari2 , Apurva Jain3 , Anshul Nagar4

  1. Dept. of Computer Science, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi, India.
  2. Dept. of Computer Science, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi, India.
  3. Dept. of Computer Science, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi, India.
  4. Dept. of Computer Science, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi, India.

Section:Research Paper, Product Type: Journal Paper
Volume-11 , Issue-12 , Page no. 53-55, Dec-2023

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v11i12.5355

Online published on Dec 31, 2023

Copyright © Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar . 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.

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How to Cite this Paper

IEEE Style Citation: Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar, “Face Recognition Attendance System,” International Journal of Computer Sciences and Engineering, Vol.11, Issue.12, pp.53-55, 2023.

MLA Style Citation: Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar "Face Recognition Attendance System." International Journal of Computer Sciences and Engineering 11.12 (2023): 53-55.

APA Style Citation: Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar, (2023). Face Recognition Attendance System. International Journal of Computer Sciences and Engineering, 11(12), 53-55.

BibTex Style Citation:
@article{Goel_2023,
author = {Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar},
title = {Face Recognition Attendance System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2023},
volume = {11},
Issue = {12},
month = {12},
year = {2023},
issn = {2347-2693},
pages = {53-55},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5648},
doi = {https://doi.org/10.26438/ijcse/v11i12.5355}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v11i12.5355}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5648
TI - Face Recognition Attendance System
T2 - International Journal of Computer Sciences and Engineering
AU - Prachi Goel, Abdul Aleem Ansari, Apurva Jain, Anshul Nagar
PY - 2023
DA - 2023/12/31
PB - IJCSE, Indore, INDIA
SP - 53-55
IS - 12
VL - 11
SN - 2347-2693
ER -

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Abstract

In today’s digital era, face recognition systems have emerged as a vital component across various sectors. As one of the most commonly used biometric technologies, face recognition offers a multitude of advantages including security, authentication, and identification. Despite its lower accuracy compared to iris recognition and fingerprint recognition, face recognition continues to gain traction due to its contactless and non-invasive nature. Moreover, it can be effectively utilized for attendance marking in educational institutions and workplaces, addressing the shortcomings of traditional manual methods such as consumption and the risk of proxy attendance. This paper proposes a class attendance system based on face recognition, aiming to streamline the attendance process and eliminate its associated challenges. The system encompasses four key phases: database creation, face detection, face recognition, and attendance updation. The database is created by capturing images of students in the classroom. Face detection and recognition are performed using the Haar-Cascade classifier and Local Binary Pattern Histogram algorithm, respectively. Faces are detected and recognized in real time using live streaming videos. At the end of each session, the attendance is automatically sent via email to the respective faculty.

Key-Words / Index Term

Face Recognition, Face Detection, Haar-Cascade classifier, Local Binary Pattern Histogram, attendance system

References

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