Journal of Computing and Natural Science


Face Recognition Attendance Management System Based on Data Analytics

T. R. Lekhaa, R. Ashok Kumar, Department of IT, SNS College of Engineering, Coimbatore, Tamil Nadu, India.


Journal of Computing and Natural Science

Received On : 10 June 2021

Revised On : 18 July 2021

Accepted On : 20 October 2021

Published On : 05 April 2022

Volume 02, Issue 02

Pages : 035-037


Abstract


Face recognition systems are utilised in a variety of situations. In this digital age, every industry is affected. One of the most well-known Face recognition is one of the most widely used biometrics. It can be used for a variety of things. Among other things, security, authentication, and identification are all important. Considering its limited accuracy when compared to retina and thumbprint recognition, and because it is a popular method of identification, it is widely used. Recognition of people's faces for Attendance tracking systems can also be utilised in Educational Institutions, Organizations. Because the Current manual is outdated, It takes a long time to set up and maintain an attendance system. Fundamentally, this approach aims to establish a class attendance system Face recognition technology is used in this system. There's also the option of having a proxy attend. As a result, As a result, demand for this system is increasing. Database development, face detection, face recognition, and attendance updating are the four steps of this system.The photos of the kids in class are used to generate the database.


  1. Hapani, Smit, et al. "Automated Attendance System Using Image Processing." 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). IEEE, 2018.
  2. Akbar, Md Sajid, et al. "Face Recognition and RFID Verified Attendance System." 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE). IEEE, 2018.
  3. R.Ashok Kumar, Multi zone pedestal for ald film property correction and tunability,MP Roberts, R Chandrasekharan, P Agarwal… - US Patent App. 16/192,425, 2019
  4. Okokpujie, Kennedy O., et al. "Design and implementation of a student attendance system using iris biometric recognition." 2017 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2017.
  5. Rathod, Hemantkumar, et al. "Automated attendance system using machine learning approach." 2017 International Conference on Nascent Technologies in Engineering (ICNTE). IEEE, 2017.
  6. Siswanto, Adrian RhesaSeptian, AntoSatriyo Nugroho, and MaulahikmahGalinium. "Implementation of face recognition algorithm for biometrics based time attendance system." 2014 International Conference on ICT For Smart Society (ICISS). IEEE, 2014.
  7. Lukas, Samuel, et al. "Student attendance system in classroom using face recognition technique." 2016 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2016.
  8. https://becominghuman.ai/face-detection-using-opencv-with-haar-cascade-classifiers- 941dbb25177
  9. https://www.superdatascience.com/blogs/opencv-face-recognition
  10. T.R.Lekhaa, Networked visual servo control using cloud computing “IJMTES” volume 1 issue 3 on June 2014.
  11. Salim, Omar Abdul Rhman, Rashidah Funke Olanrewaju, and Wasiu Adebayo Balogun. "Class attendance management system using face recognition." 2018 7th International Conference on Computer and Communication Engineering (ICCCE). IEEE, 2018.
  12. International Journal of Engineering Research & Technology (IJERT) ISSN: 2278- 0181http://www.ijert.

Cite this article


T. R. Lekhaa, R. Ashok Kumar, “Face Recognition Attendance Management System Based on Data Analytics", vol.2, no.2, pp. 035-037, January 2022. doi: 10.53759/181X/JCNS202202006.


Copyright


© 2022 T. R. Lekhaa, R. Ashok Kumar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.