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Research Article

Facial Recognition Attendance System Using Python

Open Access Peer Reviewed Crossref DOI

Authors

  • Prabhat Kumar1
  • Jeevant Srivastava2
  • Nitin Srivastava3
  • Harshit Tiwari4
  • Varsha Saxena5

1234 Department of Information Technology, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India. 5 Professor of Inderprastha Engineering College, Ghaziabad, Uttar Pradesh, India.

Article Information

Published Online
May-August 2024
Pages
65-72
Article Type
Research Article
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Abstract

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Attendance marking in a school room all through a lecture isn't simplest a difficult project but additionally a time eating one at that. because of an surprisingly high variety of college students present all through the lecture there'll always be a probability of proxy attendance(s). Attendance marking with conventional methods has been an area of project. The developing need of efficient and automatic techniques of marking attendance is a growing venture within the place of face recognition. In current years, the hassle of automatic attendance marking has been broadly addressed through the usage of standard biometrics like fingerprint and Radio frequency identity tags and so on., however, these strategies lack the detail of reliability. in this proposed mission an automated attendance marking and management machine is proposed by making use of face detection and popularity algorithms. instead of the use of the conventional methods, this proposed system pursuits to increase an automatic machine that statistics the pupil's attendance by way of the use of facial popularity technology. the principle goal of this paintings is to make the attendance marking and management machine green, time saving, easy and smooth. right here faces might be recognized the usage of face popularity algorithms. The processed photo will then be compared towards the present stored document after which attendance is marked inside the database therefore. compared to present system traditional attendance marking device, this machine reduces the workload of people. This proposed gadget can be applied with 4 levels inclusive of image taking pictures, Segmentation of institution image and Face Detection, Face evaluation and popularity, Updating of Attendance in database.

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