Yüz Tanıma ile Hızlı Yoklama Alma

Yıl 2022, Sayı: 36, 78 - 86, 31.05.2022

Hakan Temiz

https://doi.org/10.31590/ejosat.1100885

Cited By: 1

Öz

Öğrencilerin sınıf ve sınav salonlarında yoklamalarını almak (YA), eğitmenler için sadece külfetli bir iş değil, aynı zamanda zaman alıcıdır. YA’da verimli ve otonom tekniklere artan bir ihtiyaç vardır. Bu makale, yüz tanımaya dayalı bir yoklama sistemini tanıtmaktadır. Geliştirilen yöntem, öğrencilerin canlı kamera görüntülerinde veya belirli bir görüntüde bulunan yüzlerini Eigen Face Recognizer algoritması ile tespit etmektedir. Yüzlerinden tespit edilen öğrencilerin yoklama bilgisi bir veri tabanına kaydedilir. Tanıma sürecinde sınıflandırıcı olarak HAAR algoritması kullanılmıştır. Deneysel çalışmalarda yüz tanıma sisteminin gerçek sınıf ortamında ortalama %79.31 doğrulukla çalıştığı gözlenmiştir. Elde edilen sonuçlar, tasarlanan sistemin, sınıf ve sınav oturumlarında otomatik kimlik doğrulama ve yoklama almada umut verici olduğunu göstermiştir. Önerilen sistem ile işaretleme, doğrulama ve kayıt işlemlerinin çok daha kısa sürede ve daha yüksek doğrulukla tamamlanabileceği de gösterilmiştir.

Anahtar Kelimeler

yoklama alma, sınıf, yüz tanıma, haar sınıflandırıcı, eigenfaces.

Rapid Marking Attendance with Face Recognition

Öz

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.

Anahtar Kelimeler

attendance marking, classroom, face recognition, haar classifier, eigenfaces

Kaynakça

• 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
• 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/
• 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).
• 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
• 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
• 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).
• 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
• 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
• González-Agulla, E., Alba-Castro, J. L., Argones-Rúa, E., & Anido-Rifón, L. (2010). Realistic Measurement Of Student Attendance İn Lms Using Biometrics. In Proc. Of The Int. Symposium On Engineering Education And Educational Technologies (Eeet’09) Y Systemics, Ciberneties And.
• Hamzah, M. L., Desnelıta, Y., Purwatı, A. A., Rusılawatı, E., Kasman, R., & Rızal, F. (2019). A Review Of Near Field Communication Technology İn Several Areas. Revista Espacios, 40(32). Retrieved From Http://Www.Revistaespacios.Com/A19v40n32/19403219.Html
• Helmi, R. A. A., Bin Eddy Yusuf, S. S., Jamal, A., & Abdullah, M. I. Bin. (2019). Face Recognition Automatic Class Attendance System (Fracas). In 2019 Ieee International Conference On Automatic Control And Intelligent Systems (I2cacıs) (Pp. 50–55). Retrieved From Https://İeeexplore.İeee.Org/İel7/8815615/8824997/08825049.Pdf
• Hooi, Y. K., Kalid, K. S., & Tachmammedov, S. (2018). Multi-Factor Attendance Authentication System. International Journal Of Software Engineering And Computer Systems, 4(2), 62–79. Retrieved From Https://Journal.Ump.Edu.My/İjsecs/Article/View/705
• Jacksi, K., Ibrahim, F., & Ali, S. (2018). Student Attendance Management System. Sch. J. Eng. Technol. Sjet, 6(2), 49–53. Retrieved From Https://Www.Researchgate.Net/Publication/323511629_Student_Attendance_Management_System
• Kainz, O., Cymbalák, D., Lamer, J., & Jakab, F. (2014). Visual System For Student Attendance Monitoring With Non-Standard Situation Detection. In 2014 Ieee 12th Ieee International Conference On Emerging Elearning Technologies And Applications (Iceta) (Pp. 221–226).
• Kar, N., Debbarma, M., Saha, A., & Pal, D. (2012). Study Of İmplementing Automated Attendance System Using Face Recognition Technique. International Journal Of Computer And. Retrieved From Https://Scholar.Google.Com/Citations?View_Op=View_Citation&Continue=/Scholar%3fhl%3dtr%26as_Sdt%3d0,5%26scilib%3d1025&Citilm=1&Citation_For_View=Nz9wıjaaaaaj:U5hhmvd_Uo8c&Hl=Tr&Oi=P
• Kassim, M., Mazlan, H., Zaini, N., & Salleh, M. K. (2012). Web-Based Student Attendance System Using Rfıd Technology. In 2012 Ieee Control And System Graduate Research Colloquium (Pp. 213–218). Retrieved From Https://Www.Researchgate.Net/Profile/Nur-Huda-Mohd-Amin-2/Publication/259079462_Stability_Study_Of_Pd_And_Pı_Controllers_İn_Multiple_Difference_Disturbances/Links/00463529ea15559e06000000/Stability-Study-Of-Pd-And-Pı-Controllers-İn-Multiple-Difference-Dis
• Kawaguchi, Y., Shoji, T., Lin, W., Kakusho, K., & Minoh, M. (2005). Face Recognition-Based Lecture Attendance System. In The 3rd Aearu Workshop On Network Education (Pp. 70–75).
• Kişisel Verilerin Korunması Kanunu. (N.D.). Retrieved From Https://Www.Mevzuat.Gov.Tr/Mevzuatmetin/1.5.6698.Pdf
• Kommey, B., Anyane-Lah, O., & Amuzu, W. E. (2018). Swyfttapp: An Nfc Based Attendance System Using Fingerprint Authentication. International Journal Of Engineering, Science And Technology, 10(1), 23–39. Retrieved From Https://Www.Ajol.İnfo/İndex.Php/İjest/Article/View/167077/156514
• Krishnan, M. G., & Balaji, S. B. (2015). Implementation Of Automated Attendance System Using Face Recognition. International Journal Of Scientific \& Engineering Research, 6(3), 30–33.
• Kumbhar, A. A., Wanjara, K. S., Trivedi, D. H., Khairatkar, A. U., & Sharma, D. (2014). Automated Attendance Monitoring System Using Android Platform. International Journal Of Current Engineering And Technology, 4(2), 1096–1099. Retrieved From Https://Asset-Pdf.Scinapse.İo/Prod/2550182481/2550182481.Pdf
• Lim, T. S., Sim, S. C., & Mansor, M. M. (2009). Rfıd Based Attendance System. In 2009 Ieee Symposium On Industrial Electronics \& Applications (Vol. 2, Pp. 778–782).
• Lukas, S., Mitra, A. R., Desanti, R. I., & Krisnadi, D. (2016). Student Attendance System İn Classroom Using Face Recognition Technique. In 2016 International Conference On Information And Communication Technology Convergence (Ictc) (Pp. 1032–1035).
• Mane, S., Tikka, K., Deshpande, G., & Toke, S. (2019). Smart Attendance And Location Tracking Using Iot. Int. J. Eng. Res. Technol.(Ijert), 11(8), 681–683. Retrieved From Https://Www.İjert.Org/Smart-Attendance-And-Location-Tracking-Using-İot
• Mohandes, M. A. (2017). Class Attendance Management System Using Nfc Mobile Devices. Intelligent Automation \& Soft Computing, 23(2), 251–259. Retrieved From Https://Www.Tandfonline.Com/Doi/Abs/10.1080/10798587.2016.1204749
• Nayır, F. (2017). The Relationship Between Student Motivation And Class Engagement Levels. Eurasian Journal Of Educational Research, 17, 59–78. Retrieved From Https://Dergipark.Org.Tr/Tr/Pub/Ejer/İssue/42485/511749#Article_Cite
• Özcan, C., Saray, F., & Mustafa, T. (2018). Mobil Cihazlar İçin Rfıd & Bluetooth Düşük Enerji Teknolojisi İle Öğrenci Yoklama Sistemi Tasarımı. International Journal Of Multidisciplinary Studies And Innovative Technologies, 2(1), 26–30. Retrieved From Https://Dergipark.Org.Tr/En/Download/Article-File/495425
• Patel, U. A., & Priya, S. (2014). Development Of A Student Attendance Management System Using Rfıd And Face Recognition: A Review. International Journal Of Advance Research İn Computer Science And Management Studies, 2(8), 109–119.
• Patil, A., & Shukla, M. (2014). Implementation Of Classroom Attendance System Based On Face Recognition İn Class. International Journal Of Advances İn Engineering \& Technology, 7(3), 974.
• Qureshi, M. (2020). The Proposed İmplementation Of Rfıd Based Attendance System. International Journal Of Software Engineering \& Applications (Ijsea), 11(3).
• Radzı, S. A., Hanı, M. K., & Bakhterı, R. (2016). Finger-Vein Biometric İdentification Using Convolutional Neural Network. Turkish Journal Of Electrical Engineering And Computer Science, 24, 1863–1878.
• Sawhney, S., Kacker, K., Jain, S., Singh, S. N., & Garg, R. (2019). Real-Time Smart Attendance System Using Face Recognition Techniques. In 2019 9th International Conference On Cloud Computing, Data Science \& Engineering (Confluence) (Pp. 522–525).
• Sezdi, E., & Tüysüz, B. (2018). Elektronik Bilgi Sistemleri Tabanlı Öğrenci Yoklama Kontrol Sistemi. Bilgi Yönetimi, 1(1), 23–31. Retrieved From Chrome-Extension://Efaidnbmnnnibpcajpcglclefindmkaj/Viewer.Html?Pdfurl=Https%3a%2f%2fdergipark.Org.Tr%2ftr%2fdownload%2farticle-File%2f482374&Chunk=True
• Turk, M., & Pentland, A. (1991). Eigenfaces For Recognition. Journal Of Cognitive Neuroscience, 3(1), 71–86.
• Uğuz, S., & Turan, Ş. (2021). Parmak İzine Dayalı Taşınabilir Özellikli Öğrenci Yoklama Sistemi Geliştirilmesi. El-Cezeri, 8, 36–44. Https://Doi.Org/10.31202/Ecjse.755754
• Vyas, R., Kanumurı, T., Sheoran, G., & Dubey, P. (2019). Efficient Features For Smartphone-Based İris Recognition. Turkish Journal Of Electrical Engineering And Computer Science, 27, 1589–1602.
• Yalçın, N., & Gürbüz, F. (2015). Biyometrik Güvenlik Sistemlerinin İncelenmesi. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, 3, 398–413.
• Yang, H., & Han, X. (2020). Face Recognition Attendance System Based On Real-Time Video Processing. Ieee Access, 8, 159143–159150. Retrieved From Https://İeeexplore.İeee.Org/Stamp/Stamp.Jsp?Arnumber=9138372
• Zainal, N. I., Sidek, K. A., Gunawan, T. S., Manser, H., & Kartiwi, M. (2014). Design And Development Of Portable Classroom Attendance System Based On Arduino And Fingerprint Biometric. In The 5th İnternational Conference On İnformation And Communication Technology For The Muslim World (Ict4m) (Pp. 1–4). Retrieved From Http://Www.İiisci.Org/Journal/Pdv/Sci/Pdfs/Xq914co.Pdf