Student Attendance System Using Biometric System

Aremu Idris Abiodun; Ebole Friday Alpha; Odesanya Olufunsho Idowu

doi:doi:10.11648/j.mcs.20220703.11

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Student Attendance System Using Biometric System

Aremu Idris Abiodun, Ebole Friday Alpha, Odesanya Olufunsho Idowu

Published in Mathematics and Computer Science (Volume 7, Issue 3)

Received: 26 October 2021 Accepted: 30 December 2021 Published: 12 May 2022

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Abstract

Attendance is an essential aspect of learning process in every tertiary institution. Attendance taking in every class is a day to day activity in a tertiary institutions and organisations. The traditional ways of taken the student attendance by signing of papers or calling of students name in the class is also time consuming and unconfident. The contemporary academic procedure of repeating or calling names of student in a class attendance compete a substantial role in eminence of teaches and performance evaluation of the students. The administration of the attendance may also lead to enormous problem if administer manually. This paper intends to design attendance monitoring system using artificial intelligent. To solve the problem of attendance in class, camera will be used for capturing faces of student individually; recognize each student and update the database accordingly. Face geometry algorithm, features invariant and machine learning based methods will be applied to solve the problem. Extraction and pre-processing of face region is conducted for advanced processing. Resizing and extraction of face image involves histogram equalization and pre-processing. The image contrast is improved and clearer, since the image intensity is stretches.

Published in	Mathematics and Computer Science (Volume 7, Issue 3)
DOI	10.11648/j.mcs.20220703.11
Page(s)	32-39
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Attendance, Face Geometry, Artificial Intelligent, Face Image

References

[1]	Barkley, E. F., & Major, C. H. (2020). Student engagement techniques: A handbook for college faculty. John Wiley & Sons.
[2]	Bhattacharya, S., Nainala, G. S., Das, P., & Routray, A. (2018, July). Smart attendance monitoring system (SAMS): a face recognition based attendance system for classroom environment. In 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) (pp. 358-360). IEEE.
[3]	Andrejevic, M., & Selwyn, N. (2020). Facial recognition technology in schools: Critical questions and concerns. Learning, Media and Technology, 45 (2), 115-128.
[4]	Bagheri, M., & Movahed, S. H. (2016, November). The effect of the Internet of Things (IoT) on education business model. In 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) (pp. 435-441). IEEE.
[5]	Othman, N. A., & Aydin, I. (2018, April). A face recognition method in the Internet of Things for security applications in smart homes and cities. In 2018 6th International Istanbul Smart Grids and Cities Congress and Fair (ICSG) (pp. 20-24). IEEE.
[6]	Surekha, B., Nazare, K. J., Raju, S. V., & Dey, N. (2017). Attendance recording system using partial face recognition algorithm. In Intelligent techniques in signal processing for multimedia security (pp. 293-319). Springer, Cham.
[7]	Sawhney, S., Kacker, K., Jain, S., Singh, S. N., & Garg, R. (2019, January). Real-time smart attendance system using face recognition techniques. In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 522-525). IEEE.
[8]	Fowers, J., Ovtcharov, K., Papamichael, M., Massengill, T., Liu, M., Lo, D.,... & Burger, D. (2018, June). A configurable cloud-scale DNN processor for real-time AI. In 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture (ISCA) (pp. 1-14). IEEE.
[9]	Emetere, M. E., & Akinlabi, E. T. (2020). Introduction to environmental data analysis and modeling (Vol. 58). Springer Nature.
[10]	Sotonwa, K., & Oyeniran, O. (2019). Facial Recognition System: A Shift In Students Attendance Management. psychology, 100, 10.
[11]	Rekha, E., & Ramaprasad, P. (2017, January). An efficient automated attendance management system based on Eigen Face recognition. In 2017 7th International Conference on Cloud Computing, Data Science & Engineering-Confluence (pp. 605-608). IEEE.
[12]	Steiner, H., Sporrer, S., Kolb, A., & Jung, N. (2016). Design of an active multispectral SWIR camera system for skin detection and face verification. Journal of Sensors, 2016.
[13]	Rathod, H., Ware, Y., Sane, S., Raulo, S., Pakhare, V., & Rizvi, I. A. (2017, January). Automated attendance system using machine learning approach. In 2017 International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-5). IEEE.
[14]	Wang, D., Fu, R., & Luo, Z. (2017). Classroom attendance auto-management based on deep learning. Advances in Social Science, Education and Humanities Research, 123.
[15]	Fernández, A., García, S., Galar, M., Prati, R. C., Krawczyk, B., & Herrera, F. (2018). Learning from imbalanced data sets (Vol. 10, pp. 978-3). Berlin: Springer.
[16]	Lei, Z., Bai, Q., He, R., & Li, S. Z. (2008, June). Face shape recovery from a single image using cca mapping between tensor spaces. In 2008 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-7). IEEE.

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APA Style

Aremu Idris Abiodun, Ebole Friday Alpha, Odesanya Olufunsho Idowu. (2022). Student Attendance System Using Biometric System. Mathematics and Computer Science, 7(3), 32-39. https://doi.org/10.11648/j.mcs.20220703.11

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ACS Style

Aremu Idris Abiodun; Ebole Friday Alpha; Odesanya Olufunsho Idowu. Student Attendance System Using Biometric System. Math. Comput. Sci. 2022, 7(3), 32-39. doi: 10.11648/j.mcs.20220703.11

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AMA Style

Aremu Idris Abiodun, Ebole Friday Alpha, Odesanya Olufunsho Idowu. Student Attendance System Using Biometric System. Math Comput Sci. 2022;7(3):32-39. doi: 10.11648/j.mcs.20220703.11

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@article{10.11648/j.mcs.20220703.11,
  author = {Aremu Idris Abiodun and Ebole Friday Alpha and Odesanya Olufunsho Idowu},
  title = {Student Attendance System Using Biometric System},
  journal = {Mathematics and Computer Science},
  volume = {7},
  number = {3},
  pages = {32-39},
  doi = {10.11648/j.mcs.20220703.11},
  url = {https://doi.org/10.11648/j.mcs.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20220703.11},
  abstract = {Attendance is an essential aspect of learning process in every tertiary institution. Attendance taking in every class is a day to day activity in a tertiary institutions and organisations. The traditional ways of taken the student attendance by signing of papers or calling of students name in the class is also time consuming and unconfident. The contemporary academic procedure of repeating or calling names of student in a class attendance compete a substantial role in eminence of teaches and performance evaluation of the students. The administration of the attendance may also lead to enormous problem if administer manually. This paper intends to design attendance monitoring system using artificial intelligent. To solve the problem of attendance in class, camera will be used for capturing faces of student individually; recognize each student and update the database accordingly. Face geometry algorithm, features invariant and machine learning based methods will be applied to solve the problem. Extraction and pre-processing of face region is conducted for advanced processing. Resizing and extraction of face image involves histogram equalization and pre-processing. The image contrast is improved and clearer, since the image intensity is stretches.},
 year = {2022}
}

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TY  - JOUR
T1  - Student Attendance System Using Biometric System
AU  - Aremu Idris Abiodun
AU  - Ebole Friday Alpha
AU  - Odesanya Olufunsho Idowu
Y1  - 2022/05/12
PY  - 2022
N1  - https://doi.org/10.11648/j.mcs.20220703.11
DO  - 10.11648/j.mcs.20220703.11
T2  - Mathematics and Computer Science
JF  - Mathematics and Computer Science
JO  - Mathematics and Computer Science
SP  - 32
EP  - 39
PB  - Science Publishing Group
SN  - 2575-6028
UR  - https://doi.org/10.11648/j.mcs.20220703.11
AB  - Attendance is an essential aspect of learning process in every tertiary institution. Attendance taking in every class is a day to day activity in a tertiary institutions and organisations. The traditional ways of taken the student attendance by signing of papers or calling of students name in the class is also time consuming and unconfident. The contemporary academic procedure of repeating or calling names of student in a class attendance compete a substantial role in eminence of teaches and performance evaluation of the students. The administration of the attendance may also lead to enormous problem if administer manually. This paper intends to design attendance monitoring system using artificial intelligent. To solve the problem of attendance in class, camera will be used for capturing faces of student individually; recognize each student and update the database accordingly. Face geometry algorithm, features invariant and machine learning based methods will be applied to solve the problem. Extraction and pre-processing of face region is conducted for advanced processing. Resizing and extraction of face image involves histogram equalization and pre-processing. The image contrast is improved and clearer, since the image intensity is stretches.
VL  - 7
IS  - 3
ER  -

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Author Information

Aremu Idris Abiodun

Department of Computer Science, Lagos State Polytechnic, Ikorodu, Nigeria
Ebole Friday Alpha

Department of Computer Science, Lagos State Polytechnic, Ikorodu, Nigeria
Odesanya Olufunsho Idowu

Department of Computer Science, Lagos State Polytechnic, Ikorodu, Nigeria

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Plain Text BibTeX RIS

APA Style

Aremu Idris Abiodun, Ebole Friday Alpha, Odesanya Olufunsho Idowu. (2022). Student Attendance System Using Biometric System. Mathematics and Computer Science, 7(3), 32-39. https://doi.org/10.11648/j.mcs.20220703.11

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ACS Style

Aremu Idris Abiodun; Ebole Friday Alpha; Odesanya Olufunsho Idowu. Student Attendance System Using Biometric System. Math. Comput. Sci. 2022, 7(3), 32-39. doi: 10.11648/j.mcs.20220703.11

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AMA Style

Aremu Idris Abiodun, Ebole Friday Alpha, Odesanya Olufunsho Idowu. Student Attendance System Using Biometric System. Math Comput Sci. 2022;7(3):32-39. doi: 10.11648/j.mcs.20220703.11

Copy | Download

@article{10.11648/j.mcs.20220703.11,
  author = {Aremu Idris Abiodun and Ebole Friday Alpha and Odesanya Olufunsho Idowu},
  title = {Student Attendance System Using Biometric System},
  journal = {Mathematics and Computer Science},
  volume = {7},
  number = {3},
  pages = {32-39},
  doi = {10.11648/j.mcs.20220703.11},
  url = {https://doi.org/10.11648/j.mcs.20220703.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20220703.11},
  abstract = {Attendance is an essential aspect of learning process in every tertiary institution. Attendance taking in every class is a day to day activity in a tertiary institutions and organisations. The traditional ways of taken the student attendance by signing of papers or calling of students name in the class is also time consuming and unconfident. The contemporary academic procedure of repeating or calling names of student in a class attendance compete a substantial role in eminence of teaches and performance evaluation of the students. The administration of the attendance may also lead to enormous problem if administer manually. This paper intends to design attendance monitoring system using artificial intelligent. To solve the problem of attendance in class, camera will be used for capturing faces of student individually; recognize each student and update the database accordingly. Face geometry algorithm, features invariant and machine learning based methods will be applied to solve the problem. Extraction and pre-processing of face region is conducted for advanced processing. Resizing and extraction of face image involves histogram equalization and pre-processing. The image contrast is improved and clearer, since the image intensity is stretches.},
 year = {2022}
}

Copy | Download

TY  - JOUR
T1  - Student Attendance System Using Biometric System
AU  - Aremu Idris Abiodun
AU  - Ebole Friday Alpha
AU  - Odesanya Olufunsho Idowu
Y1  - 2022/05/12
PY  - 2022
N1  - https://doi.org/10.11648/j.mcs.20220703.11
DO  - 10.11648/j.mcs.20220703.11
T2  - Mathematics and Computer Science
JF  - Mathematics and Computer Science
JO  - Mathematics and Computer Science
SP  - 32
EP  - 39
PB  - Science Publishing Group
SN  - 2575-6028
UR  - https://doi.org/10.11648/j.mcs.20220703.11
AB  - Attendance is an essential aspect of learning process in every tertiary institution. Attendance taking in every class is a day to day activity in a tertiary institutions and organisations. The traditional ways of taken the student attendance by signing of papers or calling of students name in the class is also time consuming and unconfident. The contemporary academic procedure of repeating or calling names of student in a class attendance compete a substantial role in eminence of teaches and performance evaluation of the students. The administration of the attendance may also lead to enormous problem if administer manually. This paper intends to design attendance monitoring system using artificial intelligent. To solve the problem of attendance in class, camera will be used for capturing faces of student individually; recognize each student and update the database accordingly. Face geometry algorithm, features invariant and machine learning based methods will be applied to solve the problem. Extraction and pre-processing of face region is conducted for advanced processing. Resizing and extraction of face image involves histogram equalization and pre-processing. The image contrast is improved and clearer, since the image intensity is stretches.
VL  - 7
IS  - 3
ER  -

Copy | Download