Class Attendance Management System using Facial Recognition

Author:

Gomes Clyde,Chanchal Sagar,Desai Tanmay,Jadhav Dipti

Abstract

Attendance marking in a classroom during a lecture is not only a onerous task but also a time consuming one at that. 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 of efficient and automatic techniques of 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 Radio frequency 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 the 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 existing system traditional attendance marking system, this system reduces the workload of people. This proposed system will be implemented with 4 phases such as Image Capturing, Segmentation of group image and Face Detection, Face comparison and Recognition, Updating of Attendance in database.

Publisher

EDP Sciences

Subject

General Medicine

Reference10 articles.

1. Radhika C.Damale, Prof.Bageshree.V.Pathak. ”Face Recognition Based Attendance System Using Machine Learning Algorithms.” Proceedings of the Second International Conference on Intelligent Computing and Control Systems (ICICCS 2018) IEEE Xplore Compliant Part Number: CFP18K74-ART; ISBN:978-1-5386-2842-3. IEEE 2018

2. Omar Abdul, Rhman Salim, Rashidah Funke Olan-rewaju, Wasiu Adebayo Balogun. “ Class Attendance Management System Using Face Recognition.” 2018 7th International Conference on Computer and Communication Engineering (ICCCE) IEEE 2018.

3. Adrian Rhesa Septian Siswanto, Anto Satriyo Nu-groho, Maulahikmah Galinium. “Implementation of Face Recognition Algorithm for Biometrics Based Time Attendance System” Center for Information Communication Technology Agency for the Assessment Application of Technology (PTIK-BPPT) Teknologi 3 BId., 3F, PUSPIPTEK Serpong, Tangerang, INDONESIA, 15314.

4. Jinsu Kim, Usman Cheema, Seungbin Moon. “,Face Recognition Enhancement by Employing Facial Component Classification and Reducing the Candidate Gallery Set. Department of Computer Engineering, Sejong University, Seoul, 143-747, Korea (sb-moon@sejong.ac.kr).

5. Nusrat Mubin Ara, Nishikanto Sarkar Simul, Md. Saiful Islam.” “Convolutional Neural Network(CNN) Approach for Vision Based Student Recognition System.” 2017 20th International Conference of Computer and Information Technology (ICCIT), 22-24 December, 2017.

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