A Face Authentication System Using Landmark Detection

Abstract

Biometric data is the key for many security applications. Authentication relies on the individual’s measurable biometric properties collected as features. In this study, a face authentication system is built to be used in opening the entrance door accessing to the apartments and housing estates. The proposed system consists of three stages. In the first stage, landmarks on the face are captured using a deep neural network. Then six selected features from the landmarks are extracted and traditional machine learning algorithms are used to authenticate users. In the last stage, a user interface is built. Face recognition tests achieved an accuracy rate of 89.79%