Face recognition attendance system project for MCA and B.Tech Final Year students

Face Recognition Based Attendance System in Python

This project is a smart attendance system that leverages face recognition technology to automate and secure the process of marking attendance. Built using Python, OpenCV, Tkinter, and SQLite, the system provides a user-friendly graphical interface for both administrators and users.

Key Features:

Face Registration: New users can register by capturing their facial images through a webcam. The system stores these images for future recognition.

Model Training: The application uses the Local Binary Patterns Histogram (LBPH) algorithm to train a face recognition model on the registered images.

Automated Attendance: During attendance, the system recognizes faces in real-time and records attendance details (ID, name, date, time) automatically.

Data Management: Attendance records are saved in both CSV files and a SQLite database, making it easy to retrieve and analyze data.

Password Protection: Sensitive operations, such as model training, are protected by a password to ensure security.

Intuitive GUI: The interface, built with Tkinter, allows users to register, train, and track attendance with ease.

Technologies Used:

- Python

- OpenCV (for face detection and recognition)

- Tkinter (for GUI)

- SQLite (for database)

- Pandas, NumPy, PIL

Benefits:

This system eliminates manual errors, speeds up the attendance process, and provides a secure and scalable solution for schools, colleges, and organizations. With its modular design, it can be extended to support advanced features like cloud integration and mobile access.

Few Screen Shots :