Face Recognition based Attendance System using KNN Algorithm

The development of automated attendance systems has occurred alongside the rise in use biometric authentication methods due to their effectiveness. The use of face recognition technology marks a shift to a more advanced and practical approach. In this paper we propose an attendance system based on face recognition using K-Nearest Neighbors (KNN) algorithm which is designed to be accurate while minimizing the need for manual work. The system uses OpenCV for face detection, a KNN model for classification, and Flask for server-side processing. The system was tested and evaluated for its real-time attendance monitoring capability with results showing that it was able to recognize users accurately with little processing power needed. The solution provided overcomes the issues presented with standard attendance systems. It guarantees scalability, non-contact interface, and difficulty to falsify which is ideal for use in educational and business settings.