Face recognition system for online examination using haar cascade
Poonam Yadav, Avjeet Singh, Geetika Sharma · 2025
Face recognition method has attracted a lot of attention nowadays as people have become very dependent on multimedia content and multimedia content is growing rapidly among people. Everyone knows that face is a unique entity and hence retains the most distinctive features for face recognition. Computer vision field has faced challenges in dealing with the difficult task of recognizing faces that are subject to pose invariance, aging, illumination and occlusion. When a face recognition system is developed, many factors come into play, and face images are one of the most compelling examples of image analysis knowledge and application. This paper developed a Face Recognition System for Online Examination using Haar Cascade technique, which aims to rectified the security and integrity of online assessments. This system uses a machine learning based object detection approach, Haar Cascade Classifier, to accurately identify and authenticate the identity of students in real-time during online examinations. The suggested system accurately recognizes faces in various lighting conditions and angles, ensuring consistent and robust performance. By incorporating face recognition into the exam process, the technology reduces the risk of impersonation and cheating, creating a secure environment for online testing. This strategy improves security and provides a scalable option for remote educational institutions.