HoG Face Detection with AES-256 Encryption

This project demonstrates a face recognition system using Histogram of Oriented Gradients (HoG) for face detection, combined with AES-256 encryption to secure the recognized face data. It is implemented in Python 3.10.0 and utilizes the DLIB library for face detection.

Features

• HoG Face Recognition: Detects faces using the Histogram of Oriented Gradients method.
• AES-256 Encryption: Encrypts the detected face data to enhance security.

Prerequisites

Before running this project, ensure you have Python 3.10.0 installed on your machine. Additionally, the DLIB library must be installed specifically for your Python version.

Step-by-Step Installation Guide

1. Clone the Repository:

   git clone https://github.com/VelkaRepo/HoG-Face-Detection-with-aes256-Encryption.git
   cd HoG-Face-Detection-with-aes256-Encryption

2. Install DLIB: DLIB is required for face recognition functionality. Install DLIB according to your Python version before proceeding. Here's how to install it:

   • For Python 3.10.0 on Windows:

     pip install dlib

   • For Python 3.10.0 on macOS or Linux: Make sure you have CMake installed, then run:

     pip install dlib

   Refer to the official DLIB installation guide for additional instructions if you encounter issues.

3. Install Dependencies: After installing DLIB, install the remaining dependencies from requirements.txt:

   pip install -r requirements.txt

4. Run the Project: Once all dependencies are installed, you can run the main script for face recognition and AES-256 encryption:

   python mainwindow.py

Explanation

This project uses the Histogram of Oriented Gradients (HoG) to detect faces in images. Once the face is detected, it can be encrypted using the AES-256 encryption method for secure storage or transmission. HoG is an efficient feature descriptor that captures edge information, while AES-256 is a symmetric encryption algorithm that provides high-level security for sensitive data.