Facial Recognition using Enhanced Facial Features k-Nearest Neighbor (k-NN) for Attendance System
Tian Xiang Tee, Hee Kooi Khoo · 2020
This paper discusses the developments of employee attendance system via face detection and facial recognition, using the enhanced featured supervised learning technique. The main goal of the proposed system, FaceAuth is to uniquely identify a person without the use of Internet connection and cloud services. The developed system can identify the face of a user using the k-nearest neighbors (k-NN) algorithm for both training and testing phases. Then, a suitable distance threshold is configured to exclude the unregistered person from the prediction. Meanwhile, it marks the attendance of individual, whenever the person's face has trained within five seconds. For 40 participants in this experiment, the developed system can achieve 92.5% in accuracy, without false positive error occur.