Image Forgery Detection Software

Version: 1.0.0

Table of Contents

1. Introduction
2. Features
3. Prerequisites
4. Installation
5. Usage
6. Contributing
7. License
8. Contact Information

1. Introduction

Welcome to our Image Forgery Detection Software, a collaborative project developed by our team to detect image forgeries using Python and MATLAB. This software combines the power of two widely used programming languages to provide an efficient and accurate image analysis solution.

Key Contributors:

• [David Vedha Jerome A]
• [Aswin k]
• [Dhruv R]
• [Dharaneesh J]
• [Dhilipan A.R]

2. Features

Our Image Forgery Detection Software is designed to offer the following key features:

• Forgery Detection: The software detects common image manipulation techniques such as copy-paste, splicing, and other forms of manipulation.
• Multi-Format Support: It can analyze images in various formats, including JPEG, PNG, and more.
• User-Friendly Interface: The software provides an intuitive command-line interface for running the detection algorithms.
• Python and MATLAB Integration: We've harnessed the capabilities of both Python and MATLAB to create a robust image analysis platform that combines their strengths.

3. Prerequisites

To run the software effectively, ensure you have the following prerequisites installed on your system:

• Python: Install Python 3.6 or higher. You can download Python from python.org.

• MATLAB: The software requires MATLAB R2017b or a newer version. You can acquire MATLAB from MathWorks.

• Python Packages: Install the following Python packages using pip:

  • NumPy
  • OpenCV
  • Pillow (Python Imaging Library)

• MATLAB Image Processing Toolbox: Ensure you have the Image Processing Toolbox installed in MATLAB.

4. Installation

Follow these steps to install the software:

1. Clone the repository to your local machine:

   git clone https://github.com/teammates/image-forgery-detection.git

2. Navigate to the project directory:

   cd image-forgery-detection

3. Ensure that you have all the prerequisites mentioned in the Prerequisites section.

5. Usage

Using our Image Forgery Detection Software is straightforward:

1. Open a command-line terminal or shell.

2. Navigate to the project directory where the software is located.

3. Run the forgery detection script using the following command:

   python forgery_detection.py input_image.jpg

   Replace input_image.jpg with the path to the image you want to analyze.

4. The software will process the image and display the results, indicating whether any forgery was detected.

6. Contributing

We appreciate contributions from the community to enhance and expand the capabilities of this software. If you'd like to contribute, please follow these guidelines:

1. Fork the repository.

2. Create a new branch for your feature or bug fix.

3. Implement your changes, ensuring that you document your code.

4. Thoroughly test your changes.

5. Submit a pull request, providing details of the changes you've made.

7. License

Our Image Forgery Detection Software is released under the MIT License. You are welcome to use, modify, and distribute it as needed. However, please provide credit to the original authors and retain the license text in your project.

Thank you for using our software. We hope it assists you in detecting image forgeries effectively.