Abstract
This paper provides a comprehensive exploration of the underlying principles, real-world applications, existing limitations, and prospective advancements in face recognition technology, emphasizing the need for secure and ethical implementation in modern digital ecosystems.Face recognition technology has emerged as a transformative innovation in the field of biometric authentication, offering a reliable, efficient, and non-invasive method for personal identification and verification. By leveraging advancements in computer vision and deep learning—particularly Convolutional Neural Networks (CNNs)—this technology enables the detection, extraction, and comparison of unique facial features from static images and real-time video streams. The facial recognition process typically involves key stages such as face detection, feature mapping, and encoding of facial landmarks into numerical embeddings, which are then matched against a pre-existing database for identification or verification purpo