Secure And Real-Time 1-To-N Face Recognition System For Web-Based User Authentication

Abstract

Traditional authentication mechanisms primarily rely on textual credentials such as usernames, passwords, or identification numbers. These approaches are prone to security risks including password theft, guessing attacks, and user forgetfulness. Although face recognition has been explored as an alternative many existing solutions depend on static image storage or manual verification, which limits automation and real-time usability. Furthermore, such systems often lack dynamic retrieval of user-specific information, leading to inefficient and less secure identification processes.To address these limitations, this paper proposes a real-time face capture and identification framework integrated with OpenCV for intelligent user authentication. During the registration phase, the system captures facial data live through a web-based interface connected to a webcam using OpenCV. The acquired facial images are securely stored in the server-side database or file system. During authentication, a new live image is captured and processed using face similarity algorithms to compare it with previously stored templates. Once a match is confirmed, the system dynamically retrieves associated user details from the database and presents them securely on the interface.The proposed architecture combines real-time camera integration, secure storage mechanisms, and efficient facial comparison techniques to provide reliable identity verification. By ensuring that access is granted only to authenticated individuals, the system enhances security while improving usability. The modular design allows seamless deployment in modern web-based applications requiring automated and intelligent authentication.