Secure Face Recognition Attendance System
This project demonstrates how a face recognition model can be integrated into a real-world attendance application. The system uses a React interface connected to a FastAPI backend to process live frames, verify user identity, and detect whether the presented face is real or spoofed. The prototype highlights how face recognition and anti-spoofing can work together to create a more secure and efficient attendance workflow.
The Challenge
Manual attendance tracking can be slow, error-prone, and difficult to manage at scale. Basic face recognition systems can also be vulnerable to spoofing attempts using printed images, screens, or fake facial inputs. This project addresses both problems by combining automated identity verification with anti-spoofing detection.
The Solution
The solution provides a frontend interface for capturing or sending face frames to the backend. The FastAPI backend processes the input using face recognition and anti-spoofing models, verifies the identity, checks whether the face is real, and returns the result to the interface. This creates a secure attendance prototype that can be extended into a full real-time system.
Architecture
The system consists of a React.js frontend, a FastAPI backend, and AI models for face recognition and spoof detection. The frontend sends captured frames to the backend API. The backend runs preprocessing, identity verification, and anti-spoofing checks, then returns attendance decisions to the user interface.