This project is an attendance system that leverages facial recognition technology for efficient and secure attendance tracking. The key features and implementations include:

• Face Detection: Utilizes the haarcascade classifier for accurate face detection in images or video streams.
• Face Recognition: Implements algorithms for recognizing and identifying individuals based on their facial features.
• Training Image Generation: Generates training images for the facial recognition system, enabling it to learn and improve its recognition capabilities.
• Attendance Storage: Stores attendance records in Excel files, providing a structured and easily accessible format for data management.

The project employs OpenCV, a powerful computer vision library, for image processing and computer vision tasks. It combines robust algorithms with user-friendly interfaces to provide a seamless experience for attendance tracking.

Through this project, you will gain hands-on experience in developing facial recognition systems, working with computer vision techniques, and integrating data storage and management solutions.

Skills Utilized:

• Facial Recognition
• Attendance Tracking
• OpenCV
• Image Processing
• Computer Vision
• Data Storage and Management
• Excel File Handling

This project demonstrates proficiency in computer vision, image processing, and facial recognition techniques, while also showcasing the ability to develop practical and efficient attendance management solutions.

Automated Attendance System with Facial Recognition

Table of Contents

1. Introduction
2. Advantages of Facial Recognition
3. Technical Details
4. User Registration
5. Marking Attendance
6. Project Overview
7. Screenshots
8. Video Demos

Introduction

This automated attendance system utilizes facial recognition technology to replace traditional attendance methods, making it more efficient and hygienic. It provides numerous advantages in various applications, such as attendance recording, access control, and surveillance.

Advantages of Facial Recognition

• Automated Time Tracking System
• Cost Effective
• Touchless Sign in System
• More accurate Worker Attendance
• Strengthens security measures

Technical Details

Facial recognition technology involves face detection, data transformation, and face matching. It provides accurate identification and verification based on facial features.

User Registration

To use the system, users register themselves using a real-time camera. The system detects their face and creates a dataset folder containing user images. Users can also provide additional details such as their roll number and name.

Marking Attendance

Users can mark their attendance by clicking the “Register Attendance” button. The real-time camera detects the user’s face and matches it with the data stored in the dataset folder. If there’s a match, attendance data is recorded in an Excel sheet, including the user’s ID, name, date, and time.

Project Overview

Creating this project involved a deep dive into image processing and artificial intelligence. It covered image capture, face detection, dataset management, feature extraction, and recognition algorithms. This project allowed us to gain practical experience in software development and AI.

Screenshots

Video Demos