Araştırma Makalesi

Rapid Marking Attendance with Face Recognition

Sayı: 36 31 Mayıs 2022
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Rapid Marking Attendance with Face Recognition

Abstract

Marking attendance (MA) of students in the classroom and exam halls is not only a burdensome task for the instructors, but it is also time consuming. There is a growing need for efficient and autonomous techniques in AM. This article introduces an attendance system based on face recognition. The developed method detects the students exploiting their faces present in live camera images or in a given image through the Eigen Face Recognizer algorithm. After then, students are recognized and their attendance information recorded in an offline database. HAAR algorithm is used as a classifier in recognition process. In the experimental studies, it has been observed that the face recognition system works with an average accuracy of 79.31% in the real classroom environment. The obtained results showed that the designed system is promising for automatic authentication and marking attendance in classroom and exam sessions. It has been also shown that with the proposed system, marking, authentication and recording works can be completed in a much shorter time and with higher accuracy.

Keywords

Kaynakça

  1. Aydın, Ö., & Dalkılıç, F. (2018). Üniversite Öğrencilerinin Ders Devamlarının Takibine Yönelik Bilgi Sistemi. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, 20(60), 863–875. Retrieved From Https://Dergipark.Org.Tr/En/Download/Article-File/629339
  2. Bhattacharya, S., Nainala, G. S., Das, P., & Routray, A. (2018). 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). Biwebauth (Bwa). (N.D.). Retrieved From Https://Sourceforge.Net/Projects/Biowebauth/Files/Biowebauth/
  3. Bouchard, G., & Triggs, B. (2005). Hierarchical Part-Based Visual Object Categorization. In 2005 Ieee Computer Society Conference On Computer Vision And Pattern Recognition (Cvpr’05) (Vol. 1, Pp. 710–715).
  4. Çetinel, G., Çerkezi, L., Yazar, B., & Eroğlu, D. (2016). Hybrid Biometric System Using Iris And Speaker Recognition. International Journal Of Applied Mathematics Electronics And Computers. Selçuk Üniversitesi. Https://Doi.Org/10.18100/İjamec.270332
  5. Chew, C. B., Mahinderjit-Singh, M., Wei, K. C., Sheng, T. W., Husin, M. H., & Malim, N. (2015). Sensors-Enabled Smart Attendance Systems Using Nfc And Rfıd Technologies. Int. J. New Comput. Archit. Appl, 5, 19–29. Retrieved From Https://Www.Researchgate.Net/Profile/Natalie-Walker-15/Publication/301655181_Volume_5_Issue_No_1_-_International_Journal_Of_New_Computer_Architectures_And_Their_Applications_Ijncaa/Links/5720586908aefa64889a92ef/Volume-5-Issue-No-1-International-Journal-O
  6. Dalal, N., & Triggs, B. (2005). Histograms Of Oriented Gradients For Human Detection. In 2005 Ieee Computer Society Conference On Computer Vision And Pattern Recognition (Cvpr’05) (Vol. 1, Pp. 886–893).
  7. Daramola, C. Y., Folorunsho, O., Ayogu, B. A., & Adewole, L. (2019). Near Field Communication (Nfc) Based Lecture Attendance Management System On Android Mobile Platform. In International Science Conference, Nigeria (Vol. 32, Pp. 34–38). Retrieved From Http://Repository.Fuoye.Edu.Ng/Bitstream/123456789/1502/1/2019 Fuoye Conference Proceedings.Pdf#Page=35
  8. Doewes, A., & Others. (2018). Student Mobile Attendance Application Using Qrcode And Integrated With Sso At Universitas Sebelas Maret. In 3rd International Conference On Creative Media, Design And Technology (Reka 2018) (Pp. 302–305). Retrieved From Https://Www.Atlantis-Press.Com/Article/25906968.Pdf

Ayrıntılar

Birincil Dil

İngilizce

Konular

Mühendislik

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

31 Mayıs 2022

Gönderilme Tarihi

9 Nisan 2022

Kabul Tarihi

16 Nisan 2022

Yayımlandığı Sayı

Yıl 2022 Sayı: 36

Kaynak Göster

APA
Temiz, H. (2022). Rapid Marking Attendance with Face Recognition. Avrupa Bilim ve Teknoloji Dergisi, 36, 78-86. https://doi.org/10.31590/ejosat.1100885

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