Open AccessStudents Attendances System Using Face Recognition
Author(s) -
Prof. Roshan R. Kolte
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.39392
Subject(s) - computer science , facial recognition system , haar like features , attendance , classifier (uml) , mistake , artificial intelligence , biometrics , face detection , support vector machine , machine learning , face recognition grand challenge , computer vision , pattern recognition (psychology) , law , political science , economics , economic growth
Now a days we are living in this world where everything is automated and linked online. Internet are the things discover and it is used all over a world very beneficially.in human body face is the crucial factor for identifying each person. It can be identified by using different method like biometric for taking attendance. But in this method many more time are required to take attendance and also people are in contact with each other while marking their attendance in this pandemic situation we are introducing new technology student attendance system using face reorganization. Generally in a classroom the attendance was taken manually at ending or beginning of the class. The problem is that they required a lot of time to be taken and some manual and paper work will make a chance of mistake. To overcome from this problem we are introducing face recognition base attendance system. It is used in many application for identification of human face in a digital image or live video stream video. The proposed system make used of Haar classifier, KNN, CNN, SVM and global filters. After this recognition attendance report will be generated in excel format. The overall accuracy and complexity are calculated after testing this system it is cost efficient and need less installation time. Keywords: Face recognitions, Face detection, Haar classifier, CNN, KNN, SVM, LBPH, Automatic Attendances and image processing.