An Automated Attendance System Using Face Recognition Technique based on Haar Cascade with LBPH

In educational institutions, attendance used to be manually recorded on attendance sheets. This method doesn't work since substitute pupils can easily use them. This study introduces a face recognition-based automated attendance system that uses an image of the entire classroom to determine students' presence by matching their faces to a trained set. Everyone's faces are captured by a camera positioned in the classroom and sent to this system, which analyses them to find and recognize individual faces as well as log attendance in the main database. By capturing features on images, the Haar Cascade classifier was used to detect faces, and the Local Binary Pattern Histogram (LBPH) was used to recognize faces. This system is capable of recognizing students even if they are wearing glasses or have a beard.