EMPLOYEE RETENTION STRATEGIES OF GARMENTS INDUSTRY IN TIRUPUR CITY

The Face -Based Attendance System is an innovative solution designed to automate and streamline the process of recording attendance in academic institutions and workplaces. Traditional methods, such as manual sign-ins and RFID-based systems, are often time-consuming and susceptible to proxy attendance. This project leverages advanced computer vision and machine learning techniques, particularly using Open CV and the Haar Cascade Classifier, to detect and recognize faces in real time. The system captures live video input through a webcam, processes the facial features, and matches them with stored profiles to mark attendance automatically. This approach not only improves accuracy and efficiency but also enhances security and reduces administrative overhead. The system is implemented using Python and integrates a graphical user interface (GUI) for ease of use. Overall, this project demonstrates the potential of facial recognition technology in creating smart, secure, and contact-less attendance systems. Keywords: Face recognition, attendance system, computer vision, machine learning, OpenCV, Haar Cascade Classifier, real-time detection, Python, automation, contactless attendance.