Review Paper on Face Recognition-based Attendance System

The Attendance System performs image and class training that enables OpenCV data extraction functionality. The central objective behind this project involves building Face Recognition technology for attendance management to transform existing manual procedures into new automated systems. The system operates within the classroom space to train student with information that consists of name along with roll number and class details and sections and images. The extraction of images occurred through OpenCV software. When the corresponding class period began students would approach the machine for a photo capture session against the registered database photos. The development of a facial recognition-based attendance solution through Raspberry Pi forms the main objective of this project. The integration of face recognition algorithms in this system removes the requirement for manual user contact and achieves better precision levels together with enhanced dependability. The system first recognizes faces through its capture function and then creates records about attendance while determining presence as well as absence based on time spent in front of the system. The application features Face Detection and Face Recognition functionalities conducted through the Haar Cascade classifier using Open CV algorithms executed on Raspberry Pi hardware. Key Words: Face Detection, Face Recognition, HaarCascade classifier, Open CV, Raspberry Pi