When it comes to the most productive image processing application, face recognition considered to be the most reliable one and its role in technical field is incredible. Attendance marking system using face recognition is a procedure of marking attendance of student via matching face of a student with their stored biometric facial measurements. This system is developed to remove the pen paper marking attendance to save time, energy and increase accuracy. What method we are using nowadays to mark attendance is tedious and time-energy consuming. Attendance records can be easily manipulated because of lenient security but this system store attendance record in excel sheet in database of computer which is more secure than normal method of marking attendance. Teachers won't be carrying attendance record with them daily; extra burden will be reduced. The system will be tested under various parameter like illumination, variation of the distance between student and camera, head movement etc. After all this testing, accuracy and productivity of system can be finalized. The proposed system provides efficient way of marking attendance. This system can be used mark attendance with mask too. Also, multiple student attendance can be marked, hence reducing time and efforts.
Keywords
Python, Face recognition, OpenCV, Dlib, CMake, Numpy.
Lukas, Samuel, et al. "Student attendance system in classroom using face recognition technique." 2016 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2016.
R. Girshick, “Fast R-CNN,” in IEEE International Conference on Computer Vision (ICCV), 2015.
Xiaofei He; Shuicheng Yan; Yuxiao Hu; Niyogi, P.; Hong-Jiang Zhang, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 328 340, 2005.
Michał Dolecki, Paweł Karczmarek, Adam Kiersztyn, Witold Pedrycz, "Face recognition by humans performed on basis of linguistic descriptors and neural networks", Neural Networks (IJCNN) 2016 International Joint Conference on, pp. 5135-5140, 2016, ISSN 2161-4407.
K. Puthea, R. Hartanto, and R. Hidayat, “The Attendance Marking System based on Eigenface Recognition using OpenCV and Python,” Journal of Physics: Conference Series, vol. 1551, no. 1, p. 012012, May 2020, doi: 10.1088/1742-6596/1551/1/012012.
“Face Detection And Recognition Using Python And OpenCV,” Journal of Xidian University, vol. 15, no. 7, Jul. 2021, doi: 10.37896/jxu15.7/008.
C. Md. Mizan, “Real-time Face Recognition System using Python and OpenCV,” INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, vol. 06, no. 05, May 2022, doi: 10.55041/ijsrem13420.
H. Nagoriya, “Attendance System using Face Recognition utilizing OpenCV Image Processing Library,” International Journal for Research in Applied Science and Engineering Technology, vol. 8, no. 6, pp. 1811–1814, Jun. 2020, doi: 10.22214/ijraset.2020.6297.
S. Khan, A. Akram, and N. Usman, “Real Time Automatic Attendance System for Face Recognition Using Face API and OpenCV,” Wireless Personal Communications, vol. 113, no. 1, pp. 469–480, Mar. 2020, doi: 10.1007/s11277-020-07224-2.
K. Mridha and N. T. Yousef, “Study and Analysis of Implementing a Smart Attendance Management System Based on Face Recognition Tecqnique using OpenCV and Machine Learning,” 2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT), Jun. 2021, doi: 10.1109/csnt51715.2021.9509614.
Cite this article
Smriti, Janhavi Joshi, Priyanka M, Usha B, “Face Recognition Based Attendance System Using OpenCV Python”, Advances in Intelligent Systems and Technologies, pp. 052-056, December. 2022. doi: 10.53759/aist/978-9914-9946-1-2_10
