Attendance marking system using face recognition technique based on SVM and PCA

Face recognition is one of the significant techniques in computer vision that works by outputting the information about the face that was detected in the image. In this research, we proposed developing a face recognition system to automatically detect students' faces and record their attendance. The purpose of this study is to collect the students' attendance by implementing a face recognition application. The efficient face recognition method known as Principal Component Analysis has been used in this work. In addition to this, we proposed machine learning algorithms such as Support Vector Machine and Naive Bayes to classify the detected faces to match their labels. The output of our model can be exported as an excel file for further use. After our experiment with twenty-two faces, we observed that Support Vector Machine can produce a better performance, 88 percent in terms of accuracy.