Face Recognition for Attendance System Detection

Abstract

These days, biometric authentication methods begin growing rapidly as one of promising authentication methods, besides the conventional authentication method. Almost all biometrics technologies require some actions by user, which are the user needs to place funds on the scanner to set the fingers or the hand geometry detection. The user shall stand still in a fixed position in front of the camera for iris or retina identification purpose. The face recognition method has several external advantages compared to the other biometric methods because this method can be done passively without explicit action or should be held by the user since the face image can be obtained by the camera from a certain distance. This method can be especially useful for mission and supervision. This research would develop and implement the face recognition system consists of four stage process. The four-stage process were face detection process using skin color detection and Haar Cascade algorithm, alignment process that contains face features normalization process, feature extraction process, and classification process using LBPH algorithm. Furthermore, the process would be continued to current system replacement with the system that has been built. The experimental results show that the system can recognize the faces captured automatically by the camera accurately.