Paper Title : ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION

ISSN : 2394-2231
Year of Publication : 2022

10.5281/zenodo.6397284

Authors: Mr.C.Mani M.C.A.,M.Phil.,M.E., V.kirubaa

         



MLA Style: ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION " Mr.C.Mani M.C.A.,M.Phil.,M.E., V.kirubaa " Volume 9 - Issue 2 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION " Mr.C.Mani M.C.A.,M.Phil.,M.E., V.kirubaa " Volume 9 - Issue 2 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
Face recognition is the identification of humans by the unique characteristics of their Faces. Face recognition technology is the least intrusive and fastest bio- metric technology. It works with the most obvious individual identifier the human face. This research aims at providing a system to automatically record the students’ attendance during lecture hours in a hall or room using facial recognition technology instead of the traditional manual methods. The objective behind this research is to thoroughly study the field if pattern recognition (facial recognition) which is very important and is used in various applications like identification and detection. Nowadays we are facing a pandemic, there is a situation where people are not ready to wear face masks, or they do not wear them properly, so, in this research, we are introducing an automatic mask detection system using image processing and soft computing techniques to tackle this problem. In the midst of the pandemic, covering our faces with a mask has become a new normal, as face masks are active in preventing the spread of the virus. Other precautionary measures are also advocated by the government apart from covering faces, to ensure protection and hygiene. In addition, because of the limited supply of masks in the industry, millions of people are learning to make their face masks. On the opposite, identifying faces with masks on any surveillance devices would be demanding while ensuring less access control in buildings. Face coverage with masks is a problem for algorithms and success in face detection. Currently, the authorities have to manually ask people to wear masks even then they tend to fool the authorities, to avoid that we are proposing a face Machine learning-based model of recognition. In the field of computer vision, not wear a mask, they are given an alert and they would have to wear a mask.

Reference
[1] Kar, Nirmalya, et al. "Study of implementing automated attendance system using face recognition technique." International Journal of computer and communication engineering 1.2 (2012): 100. [2] RoshanTharanga, J. G., et al. "Smart attendance using real time face recognition (smart-fr)." Department of Electronic and Computer Engineering, Sri Lanka Institute of Information Technology (SLIIT), Malabe, Sri Lanka (2013). [3] Selvi, K. Senthamil, P. Chitrakala, and A. Antony Jenitha. "Face recognition based attendance marking system." Corresponding Author: S. Rajkumar*, Email: rajkumarsrajkumar@gmail. com (2014). [4] Joseph, Jomon, and K. P. Zacharia. "Automatic attendance management system using face recognition." International Journal of Science and Research (IJSR) 2.11 (2013): 327- 330. [5] Patil, Ajinkya, and Mrudang Shukla. "Implementation of classroom attendance system based on face recognition in class." International Journal of Advances in Engineering & Technology 7.3 (2014): 974. [6] Kanti, Jyotshana, and Shubha Sharm. "Automated Attendance using Face Recognition based on PCA with Artificial Neural Network." International journal of science and research IJSR(2012). [7] MuthuKalyani, K., and A. VeeraMuthu. "Smart application for AMS using face recognition." Computer Science & Engineering 3.5 (2013): 13. [8] Deshmukh, Badal J., and Sudhir M. Kharad. "Efficient Attendance Management: A Face Recognition Approach." (2014) [9] Wagh, Priyanka, et al. "Attendance system based on face recognition using eigen face and PCA algorithms." 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2015. [10] Bhattacharya, Shubhobrata, et al. "Smart Attendance Monitoring System (SAMS): A Face Recognition Based Attendance System for Classroom Environment." 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2018. [11] Samet, Refik, and Muhammed Tanriverdi. "Face recognition-based mobile automatic classroom attendance management system." 2017 International Conference on Cyberworlds (CW). IEEE, 2017. [12] Li, Xiang-Yu, and Zhen-Xian Lin. "Face recognition based on HOG and fast PCA algorithm." The EuroChina Conference on Intelligent Data Analysis and Applications. Springer, Cham, 2017. [13] Arsenovic, Marko, et al. "FaceTime—Deep learning based face recognition attendance system." 2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2017. [14] Rekha, N., and M. Z. Kurian. "Face detection in real time based on HOG." International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) 3.4 (2014): 1345-1352. [15] Kwolek, Bogdan. "Face detection using convolutional neural networks and Gabor filters." International Conference on Artificial Neural Networks. Springer, Berlin, Heidelberg, 2005

Keywords
— ATTENDANCE MANAGEMENT SYSTEM BY USING FACE RECOGNITION