Face Recognition Attendance system Introduction

The system works in four main stages: First, it creates a database by capturing and storing facial images of registered users from multiple angles. When a person needs to mark attendance, the system's high-resolution camera captures their face in real-time. The captured image then undergoes face detection using algorithms like Haar cascade to locate facial features. Advanced deep learning models like Convolutional Neural Networks (CNNs) and techniques such as Principal Component Analysis (PCA) are used to extract distinct facial features and match them against the stored database. Upon successful recognition, the system automatically records the attendance with timestamp data. The collected attendance data is stored securely and can be accessed through user-friendly interfaces for attendance tracking and management purposes.