Student Face Recognition and Alert Rule
Mr. Dipak Thongase
PG Scholar
Department of Computer Science,
G. H. Raisoni University Amravati, Maharashtra, India
Received on: 11 May ,2024 Revised on: 18 June ,2024 Published on: 29 June ,2024
Abstract: Attendance marking in a classroom during a lecture is not only an onerous task but also a time-consuming one at. Due to an unusually high number of students present during the lecture, there will always be a probability of proxy attendance(s). Attendance marking with conventional methods has been an area of challenge. The growing need for efficient and automatic techniques for marking attendance is a growing challenge in the area of face recognition. In recent years, the problem of automatic attendance marking has been widely addressed through the use of standard biometrics like fingerprint and Radiofrequency Identification tags, etc., However, these techniques lack the element of reliability. In this proposed project an automated attendance marking and management system is proposed by making use of face detection and recognition algorithms. Instead of using conventional methods, this proposed system aims to develop an automated system that records the student’s attendance by using facial recognition technology. The main objective of this work is to make the attendance marking and management system efficient, time-saving, simple, and easy. Here faces will be recognized using face recognition algorithms. The processed image will then be compared against the existing stored record and then attendance is marked in the database accordingly. Compared to the existing system traditional attendance marking system, this system reduces the workload of people. This proposed system will be implemented with 4 phases Image Capturing, Segmentation of group image and Face Detection, Face comparison and Recognition, and Updating of Attendance in the database.
Index Term – Mongo DB, React JS, Node JS, Express JS, Attendance, Facial recognition, and detection, Haar cascade, Alert, Student Face.
Doi Link – https://doi.org/10.69758/GIMRJ2406I8V12P034
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