Abstract
Student class attendance record plays an important role in most of the universities of Asia particularly countries like India. Keeping this in mind, an efficient attendance management system is proposed in this paper. This system makes use of dimensionality reduction using PCA-based face recognition algorithm incorporating Euclidean distance as the distance classifier. Faces of the students are segmented using Viola–Jones algorithm. Based on the recognized faces, attendance is updated into an Excel database. The algorithm has been tested using two different student databases. Training database is created using 50 subjects including male and female with different facial variations (15 instances per subject). Statistical data shows that an accuracy of the algorithm is greater than 99% with normal lighting conditions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Using principal component analysis and neural networks. Int. J. Comput. Netw. Wirel. Mob. Commun. (IJCNWMC) 3(1), 245–256 (2013). ISSN 2250-1568 © TJPRC Pvt. Ltd
K. Jaikumar, M. Santhosh Kumar, S. Rajkumar, A. Sakthivel, Fingerprint based student attendance system with Sms alert to parents. Int. J. Res. Eng. Technol. (IJRET) 4(2), 293–297 (2015)
D.R. Wijaya, I. Asror, Integrated and efficient attendance management system based on RFID. J. Theor. Appl. Inform. Technol. 73(1), 149–154 (2015)
Wagh, R. Thakare, J. Chaudhari, Attendance system based on face recognition using eigen face and PCA algorithms, in 2015 International Conference on Green Computing and Internet of Things (2015)
J. Wright, A.Y. Yang, A. Ganesh, S. Shankar Sastry, Y. Ma, Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 1–18 (2009)
K. Keerthi Vasan, B. Surendiran, Dimensionality reduction using principal component analysis for network intrusion detection. Persp. Sci. 8, 510–512 (2016)
G. Lakshmi Priya, M. Pandimadevi, G. Ramu Priya, P. Ramya, Implementation of attendance management system using SMART-FR. Int. J. Adv. Res. Comput. Commun. Eng. 3(11), 8532–8536 (2014)
M.K. Dabhi, B.K. Pancholi, Face detection system based on Viola–Jones algorithm. Int. J. Sci. Res. (IJSR) 5(4) (2016)
Y.-Q. Wang, An analysis of the Viola–Jones face detection algorithm. Image Process. Line 4, 128–148 (2014)
S. Bhattacharya, G.S. Nainala, P. Das, A. Routray, Smart attendance monitoring system (SAMS): a face recognition based attendance system for classroom environment, in IEEE 18th International Conference on Advanced Learning Technologies (ICALT), Mumbai (2018), pp. 358–360
Z.H. Arif, N.S. Ali, N.A. Zakaria, M.N. Al-Mhiqani, Attendance management system for educational sector: critical review. Int. J. Comput. Sci. Mob. Comput. 7(8), 60–66 (2018)
S. Sawhney, K. Kacker, S. Jain, S.N. Singh, R. Garg, Real-time smart attendance system using face recognition techniques, in 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), Noida (2019), pp. 522–525
K.N. Ashish, P. Swarnalatha, C. Prudhvi, N.J. Krishna, K.K. Sandeep, Smart attendance marking system using facial recognition. Res. J. Sci. Technol. 11(2), 101–108 (2019)
E. Rekha, P. Ramaprasad, An efficient automated management system based on eigen face recognition, in International Conference on Cloud Computing, Data Science & Engineering, 12th–13th January 2017, Amity University Uttar Pradesh, Noida, India
M.J.R. Mulla, R.P. Patil, S.K. Shah, Facial image based security system using PCA, in 2015 IEEE Access, International Conference on Information Processing (ICIP)
P. Mehta, P. Tomar, An efficient attendance management system based on face recognition using matlab and raspberry pi 2. Int. J. Eng. Technol. Sci. Res. 3(5) (2016)
P. Singh, A. Sharma, Face recognition using principal component analysis in MATLAB. Int. J. Sci. Res. Comput. Sci. Eng. 3(1) (2015)
S. Suhas, B. Kurhe Ajay, P. Khanle, Face recognition using principal component analysis and linear discriminant anlysis on holistic approach in facial images database. IOSR J. Eng. 2(12), 15–23 (2012)
S.M. Bah, F. Ming, An improved face recognition algorithm and its application in attendance management system. Elsevier Array 5, 100014 (2020)
O. Godswill1, O. Osas, O. Anderson, I. Oseikhuemen, O. Etse, Automated student attendance management system using face recognition. Int. J. Edu. Res. Inform. Sci. 5, 31–37
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Poojary, R., Milofa, M., Shruthi, K. (2021). Dimensionality Reduction Using Principal Component Analysis for Lecture Attendance Management System. In: Kalya, S., Kulkarni, M., Shivaprakasha, K.S. (eds) Advances in VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems. Lecture Notes in Electrical Engineering, vol 752. Springer, Singapore. https://doi.org/10.1007/978-981-16-0443-0_11
Download citation
DOI: https://doi.org/10.1007/978-981-16-0443-0_11
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-0442-3
Online ISBN: 978-981-16-0443-0
eBook Packages: EngineeringEngineering (R0)