Face recognition for identify verification in exams locations

This project explores the growing domain of facial recognition technology, known for accurately identifying people based on their unique facial features. This technology has gained popularity across various industries for preventing identity fraud. In the context of exam centres, where confirming...

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Bibliographic Details
Main Author: Ng, Suet Eng
Format: Final Year Project / Dissertation / Thesis
Published: 2023
Subjects:
Online Access:http://eprints.utar.edu.my/6017/
http://eprints.utar.edu.my/6017/1/fyp_IB_2023_NSE.pdf
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author Ng, Suet Eng
author_facet Ng, Suet Eng
author_sort Ng, Suet Eng
building UTAR Institutional Repository
collection Online Access
description This project explores the growing domain of facial recognition technology, known for accurately identifying people based on their unique facial features. This technology has gained popularity across various industries for preventing identity fraud. In the context of exam centres, where confirming candidates' identities is vital, facial recognition can play a crucial role. The main focus of this project is to prevent fraud in exam centres. The system's key requirement is accurately identifying individuals. It also needs to be fast for quick verification. The project uses a mix of hardware and software tools. Hardware includes cameras and laptops, meanwhile software tools include PyCharm Community, OpenCV and the Haar-Cascade Algorithm are used for development. By implementing this facial recognition system, candidates would need to identify their identity before entering exam centres, as it is to reducing cheating and impersonation. The system aims to verify candidates swiftly and accurately, improving the overall exam process. In conclusion, this project to develop a facial recognition system for exam centres is a step towards enhancing exam integrity and preventing identity fraud. Through advanced technology, the project aims to accurately identify candidates, reduce fraud, and provide insights into exam performance. It could have a big impact on education and lead to future advancements in exams and identity verification.
first_indexed 2025-11-15T19:40:31Z
format Final Year Project / Dissertation / Thesis
id utar-6017
institution Universiti Tunku Abdul Rahman
institution_category Local University
last_indexed 2025-11-15T19:40:31Z
publishDate 2023
recordtype eprints
repository_type Digital Repository
spelling utar-60172024-01-02T16:16:13Z Face recognition for identify verification in exams locations Ng, Suet Eng T Technology (General) TD Environmental technology. Sanitary engineering TR Photography This project explores the growing domain of facial recognition technology, known for accurately identifying people based on their unique facial features. This technology has gained popularity across various industries for preventing identity fraud. In the context of exam centres, where confirming candidates' identities is vital, facial recognition can play a crucial role. The main focus of this project is to prevent fraud in exam centres. The system's key requirement is accurately identifying individuals. It also needs to be fast for quick verification. The project uses a mix of hardware and software tools. Hardware includes cameras and laptops, meanwhile software tools include PyCharm Community, OpenCV and the Haar-Cascade Algorithm are used for development. By implementing this facial recognition system, candidates would need to identify their identity before entering exam centres, as it is to reducing cheating and impersonation. The system aims to verify candidates swiftly and accurately, improving the overall exam process. In conclusion, this project to develop a facial recognition system for exam centres is a step towards enhancing exam integrity and preventing identity fraud. Through advanced technology, the project aims to accurately identify candidates, reduce fraud, and provide insights into exam performance. It could have a big impact on education and lead to future advancements in exams and identity verification. 2023-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6017/1/fyp_IB_2023_NSE.pdf Ng, Suet Eng (2023) Face recognition for identify verification in exams locations. Final Year Project, UTAR. http://eprints.utar.edu.my/6017/
spellingShingle T Technology (General)
TD Environmental technology. Sanitary engineering
TR Photography
Ng, Suet Eng
Face recognition for identify verification in exams locations
title Face recognition for identify verification in exams locations
title_full Face recognition for identify verification in exams locations
title_fullStr Face recognition for identify verification in exams locations
title_full_unstemmed Face recognition for identify verification in exams locations
title_short Face recognition for identify verification in exams locations
title_sort face recognition for identify verification in exams locations
topic T Technology (General)
TD Environmental technology. Sanitary engineering
TR Photography
url http://eprints.utar.edu.my/6017/
http://eprints.utar.edu.my/6017/1/fyp_IB_2023_NSE.pdf