Face Recognition Based Attendance System

Abstract

This paper explores the use of automated technologies in the face recognition based recognition system, with a focus on automating attendance capture. The project aims to improve the attendance marking of students by providing a more personalized and efficient service through the design and implementation of a Digital Attendance Web application. A face-based recognition system is a computer-based system that utilizes image recognition technology to identify individuals. In this paper, we present a face-based recognition system that uses deep learning techniques to extract features from facial images and identify individuals.[1] The proposed system utilizes Haar Cascade to extract features from facial images, and a classifier is trained to recognize the individual in the image.[6] The system is trained on a large dataset of facial images. It achieves high accuracy in identifying individuals in different scenarios, such as variations in illumination, pose, and facial expressions. The proposed system has a wide range of applications, including security, surveillance, and identification systems. It has the potential to revolutionize the way we interact with technology and enhance the security of our personal information