Computer Vision Based Authentication and Employee Monitoring System

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Table of Contents

• Abstract
• Introduction
• Key Features
• Installation
• Usage
• Technologies Used
• Contributing
• License
• Contact

Abstract

Computer Vision Based Authentication and Employee Monitoring System is a project that utilizes computer vision techniques for secure employee authentication and monitoring. The system employs facial recognition to provide access to the company campus or specific resources. By leveraging state-of-the-art computer vision technology, the system offers enhanced security compared to traditional password-based methods.

Introduction

Computer Vision Based Authentication and Employee Monitoring System is designed to enhance security and convenience in managing employee access. The system utilizes facial recognition to authenticate employees, replacing less secure methods like password-based authentication. This repository contains the source code, documentation, and resources for the project.

Key Features

• Secure employee authentication using facial recognition.

• Admin GUI for managing employee information, training the model, and monitoring system functionality.

  1. Login GUI

     

  2. Home page GUI

     

  3. Registration User interface

     

  4. Model training

     

• Access control using a servo motor-controlled door.

  

• Guest mode for previously unregistered employees.

• Two-factor authentication with password and time-bound one-time password (OTP) sent via email.

  

• Face Detection and Recognition

  

Methodology

• System Design

  

• Algorthim flowchart

  1. registration and model training flowchart

     

  2. Face detection and Recognition flowchart

     

Installation

1. Clone this repository: git clone https://github.com/Getachew0557/Computer-Vision-Based-Authentication-and-Employee-Monitoring-System-.git
2. Install required dependencies: pip install -r requirements.txt

Usage

1. Run the main application: python main.py
2. Admins can use the GUI to manage employee information and monitor system status.
3. Employees can authenticate using their faces or request access via guest mode.

Technologies Used

• Python
• OpenCV
• SQLite
• Tkinter (GUI library)
• Raspberry Pi (system/controller)

Contributing

Contributions to this project are welcome. If you have suggestions for improvements, open issues or pull requests.

License

This project is licensed under the [Your License] License - see the LICENSE file for details.

Contact

For questions or inquiries the complate project, please contact [Getachew Getu] at getachewgetu2010gmail@gmail.com.