Online proctoring system using image processing and machine learning

K. Gopalakrishnan; N. Dhiyaneshwaran; P. Yugesh

doi:10.53730/ijhs.v6nS5.8777

Authors

K. Gopalakrishnan
kgk1969@mepcoeng.ac.in
Department of ECE, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India
N. Dhiyaneshwaran Department of ECE, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India
P. Yugesh Department of ECE, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, India

Keywords:

Continuous face recognition, Gaze tracking, Mouth open or close

Abstract

Different forms of remote education and massive online open courses are gaining reputation. The skill to proctor the online examination is a main essential factor for the scalability for promoting the students for next stage education. Existing manual monitoring is the most approaching method in education either by visually monitoring or by physically accompanying test takers to the examination centre and monitoring them. Learner’s identity verification and proctoring of online examinations is one of the main challenges in online learning systems. The migration and implementation of the online exam have been accelerated during the pandemic COVID-19. So the existing systems need a safe mechanism to authenticate and proctor online students. In this paper, we propose a system for providing the solution for authentication and proctor by using the different biometric technologies. The performance of the proposed system is evaluated by using real time videos with different scenario. The experimental results provide an improved accuracy than existing research works.

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