Intelligent College Attendance System Using Image Tagging

Abstract

In the paper, we have proposed a real-time attendance system using image tagging to overcome the wastage of time in queues for biometrics or face scanning, manual entry of attendance in the logbook and to overcome conventional manual attendance system to reduce cost and proxy attendance. Image tagging is the process of adding labels or keywords to the recognized faces or things within a certain picture. The image is processed using image segmentation and feature extraction to obtain faces and then the faces are tagged. Intelligent College Attendance system using Image tagging conducts regular attendance labeling and review tasks with a decrease in the management and control of human intervention plays a vital role in maintaining the attendance system. First, we capture an image of the whole class and stores the image in the database. In this proposed system, the faces are first detected using OpenCV's Haar cascade algorithm. The detected faces then undergo Principal Component Analysis and Local Binary Pattern algorithm to detect the student. The latest face detection and recognition technologies struggle to solve issues such as scaling, posture, lighting, variations, etc. The program proposed is designed to resolve pitfalls by providing features such as extracting of features, detection of features and analysis. We find a specific area, for instance, a classroom corner for installing the camera and checking device accuracy. The database will get automatically updated regarding the absence or presence of the student in the class.