Automatic Attendance Management System using Face Detection and Face Recognition
R. Kavitha, L.Munieswari · Journal of Emerging Technologies and Innovative Research · 2020
Image Processing is a method to perform various operations on an image, to get an enhanced image or to extract some useful information from it. Face recognition in Image Processing is the process of identifying one or more people in images or videos by analyzing and comparing patterns. In schools and colleges, the presence of the student is identified by marking the attendance. Marking the attendance manually is a difficult process. Some of the automated systems are developed to overcome these difficulties but have drawbacks like fake attendance, accuracy, etc. To overcome these drawbacks, there is a need of automated attendance system. Face recognition is one of the biometric methods to improve this system. Being a prime feature of biometric verification, facial recognition is being used enormously in several applications. The main implementation steps used in this type of system are Face Detection and Recognizing the detected face. As face is a unique identity of a person, the issue of fake attendance can be solved. The system uses Haar cascade classifier for face detection, Local Binary Pattern (LBP) for face recognition technique as it is fast, simple and has better success rate. After these, the database updates the attendance of a student as present by comparing with the student database and face database. This smart and automatic attendance system can be an constructive way to maintain the attendance records of the students in the classroom and to reduce fake attendance. This application is represented using Raspberry Pi, OpenCV and PYTHON.