Facial Recognition System with Attendance Tracking Using Python and Open CV

Abstract

In educational institutions, businesses, and offices, attendance tracking stands as a crucial daily task. Traditionally performed manually, be it through name calling or roll numbers, there is a need for a more efficient solution. This project aims to revolutionize attendance management by implementing a Face Recognition-based system. Installed in classrooms, the system captures student details like name, roll number, class, section, and photographs, utilizing OpenCV for image extraction. As students approach the device, it takes and compares pictures with a trained dataset. The process involves face identification with a Haar cascade classifier, recognition using LBPH and automatic attendance labeling. An Excel sheet is generated and updated hourly, incorporating information from the class instructor. This approach aligns with the demand for modernization and efficient time management in attendance procedures.