Paper Contents
Abstract
In the modern digital era, the demand for intelligent systems capable of automatically analyzing large volumes of image and video data has increased exponentially. Face detection and recognition technologies have emerged as vital tools for applications in security, surveillance, human-computer interaction, and identity verification. This paper presents a real-time facial detection and recognition framework utilizing OpenCV and Python libraries. The proposed system captures facial images using a webcam, processes them for feature extraction, and identifies individuals by comparing new faces against stored face prints in a database. The research highlights the importance of image quality and efficient algorithm design to achieve high accuracy. Experimental results demonstrate the systems effectiveness with an 80% recognition accuracy rate on a diverse dataset. The proposed solution offers a contactless and rapid method for identity authentication, with potential applications in online exam monitoring, border security, and access control systems.
Copyright
Copyright © 2025 Dharshika Singh. This is an open access article distributed under the Creative Commons Attribution License.
