Facial Recognition in Biometric Security: A Comparative Analysis of MATLAB and Python Implementations

Abstract

Individuals can be identified from images or video frames through the application of computer vision and machine learning technologies, specifically facial recognition. This process employs machine learning algorithms for recognition and image processing techniques to extract various features, including the distance between the eyes, the curvature of the jawline, and the contour of the nose. The image processing and computer vision capabilities of MATLAB and Open-CV libraries render them particularly suitable for the development of facial recognition applications. However, facial recognition technology has raised ethical concerns, including privacy and bias. Ethical Issues may emerge from the potential misuse of the technology and the possibility of incorrect identification, resulting from bias present in the algorithm or the training data. Developed facial recognition application's performance, metrics such as accuracy, speed, and efficiency are used. The document explores the development process of a facial recognition application through the utilization of MATLAB and Python programming languages. It delves into the ethical considerations associated with its application and examines its broader implications. across different areas like protection, advertising, and leisure. Moreover, the document outlines the software's effectiveness outcomes and contrasts it with current facial recognition systems. It offers a deeper understanding of the technical and moral considerations of facial recognition technology, its creation journey, and its possible effects on the community.