Face Recognition Based Attendance Management System Using HOG Feature Extraction and SVM Classifier
Vikrant Khadatkar, Shubhangi Bagadkar, Nutan M. Dhande · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: Face recognition system plays a vital role in almost every sector in this digital era. Face recognition is one of the popular biometrics’ techniques. It can be used for security, authentication, identification and so on. It is having low accuracy when compared to iris recognition and fingerprint recognition, but it is being widely used due to its contactless process. Face recognition technique can also be used for attendance marking field. This system targets to building a class attendance system which is used the technique of face recognition. We all know existing manual attendance system is taking more time and difficult to maintain. And having chances of proxy in attendance. That’s why, the need for this system occurs. This system consists of four phases- registration module, database creation, face detection, face recognition, attendance updating, attendance sending. Database consist of the image of the students in class. Face detection and recognition is performed using HOG feature extraction and SVM (Support Vector Machine) classifier. Faces will be detected and recognized from video streaming of the classroom. Attendance will be mailed to the respective faculty at the end of the lectures. Keywords: Face Recognition; Face Detection; SVM classifier; HOG feature extraction; attendance system;