BUILDING A COMPUTER VISION SYSTEM FOR FACIAL RECOGNITION

Facial recognition technology has gained global attention due to its potential to enhance security, identity verification, and convenience across various sectors. This study focuses on developing a facial recognition system tailored to Nigeria’s unique demographic, environmental, and technical challenges. With the country’s growing security concerns, large population, and push towards digital transformation, facial recognition is being explored as a solution for issues like identity theft, unauthorized access, and fraud. However, the effectiveness of existing systems often suffers from demographic biases and environmental factors, such as poor lighting and diverse facial features. The aim of this research is to design, develop, and evaluate a robust and inclusive facial recognition system that addresses these challenges, ensuring high accuracy, fairness, and reliability in the Nigerian context. The system will leverage deep learning techniques, including convolutional neural networks (CNNs), and will be tested across various lighting conditions, facial poses, and environmental factors. Ethical considerations, such as privacy and data security, will be incorporated to align with both local and international standards. This study intends to contribute to the development of more effective and ethically responsible facial recognition systems for Nigeria, providing a model for similar applications in other regions.