Authors: Chilufya Sydney
Abstract: This paper introduces an open-source, simplified facial recognition system intended to prevent impersonation during Zambia’s GCE exams. The system uses Python, OpenCV, and SQLite to perform two basic functions: enrolling student facial data at pre-exam registration and verifying identities in real-time at exam entrance. With a resource-poor environment perspective, the solution is affordable (<$100 per exam site equivalent to about K3,000 in Zambian currency), simple to deploy, and ethically deployed. The initiative fills significant literatures gaps concerning the flexibility of facial recognition systems in sub-Saharan African testing regimes and ethical adoption of biometric technology in schooling. Analysis of technical operational performance happens under normal lighting and equipment use through dataset-based controlled benchmarking and usability estimates rely on stakeholder evaluations. Under perfect laboratory settings, the system achieves 96.4% accuracy while delivering 87.8% accuracy at low luminance levels using 1.45 seconds for each verification process. The thesis describes the entire system development lifecycle from its inception until assessment while presenting actual field results. The system presents a practical application to enhance test security within educational institutions of developing regions. The solution delivers operational tractability alongside technical sophistication by giving an applicable solution to combat examination impersonation without exceeding existing resource capabilities.
DOI: http://doi.org/
