Real-Time Face Recognition System in Smart Classroom using Haar Cascade and Local Binary Pattern Model

The time-saving classroom technology solution is one of the main features of a smart classroom. The traditional student attendance system opens for negligence as the students can cheat by asking their friends to sign on the attendance paper. Besides, taking students’ attendance manually such as calling out names and passing out papers to be signed is time-consuming. This paper is to propose a face recognition framework for students’ attendance that can be taken in real-time using a webcam in the classroom and to develop a system where both students and lecturers can save time at the same time to smooth out the learning process. On top of that, parents or guardians also get informed about the attendance status. The face recognition system is proposed to use the Haar Cascades algorithm to detect individual faces of students while using Local Binary Pattern (L B P) is used to identify and verify students’ identity by using their facial features. This, this framework also emphasizes real-time capturing of students’ attendance, and the attendance can be taken automatically when students’ faces are detected and identified. Using 35 individuals as a sample, this paper aspires to present an effective and efficient model for the proposed system.