Machine Learning Algorithm for Developing Classroom Attendance Management System Based on Haar Cascade Frontal Face

Abstract

The face is an essential characteristic of a person; it is used to distinguish between the personalities of two or more people in the real world. In recent years, different parts of the body have been manipulated to ensure that only the right person has access to their respective accounts, both physical and virtual. Biometrics, which involves identification such as fingerprints, palm veins, DNA, palm print, and face recognition, is one of the methods that has been developed. Similarly, this study would demonstrate how to use image processing to apply facial identification and recognition algorithms to create a device that can identify and recognize the frontal faces of students in a classroom. A face is a front part of a person’s head from the forehead to the chin or the corresponding part of an animal. The face is the most significant element in human experiences since it holds important details about a person or entity. Humans have the potential to recognize others depending on their faces. This paper proposed work to develop a working prototype of a system that will facilitate class control for Technical Informatics College of Akre lecturers in a classroom by detecting the frontal faces of students from an image taken in a classroom. Face recognition and identification technologies have been established in recent years as a result of testing. Many of them are used on social networking sites, financial applications, and government offices such as the Metropolitan Police Service, Facebook, and others.