Face Recognition Based Attendance System Using Machine Learning Algorithms

The identification of person from the facial features is referred as face recognition. A facial feature can be used in the different computer vision algorithms like face detection, expression detection and many video surveillance applications. Recently, face recognition systems are attracting researchers toward it. In this approach, three different methods such as SVM, MLP and CNN have been presented. DNN is used for face detection. For SVM and MLP based approach, the features are extracted using PCA and LDA feature extraction algorithms. In CNN based approach, the images were directly feed to the CNN module as a feature vector. The proposed approach shows the good recognition accuracy for CNN based approach. The SVM, MLP and CNN achieves the testing accuracy around 87%, 86.5% and 98% on self-generated database respectively.