Digital Image Processing with Python (OpenCV) and MATLAB

Overview

This repository contains code and resources for digital image processing using Python with the OpenCV library and MATLAB. Digital image processing is a field that involves the manipulation and analysis of images to extract useful information or enhance certain features. This project focuses on leveraging the power of Python and MATLAB for various image processing tasks.

Table of Contents

• Installation
• Usage
• Examples
• Contributing
• License

Installation

Python (OpenCV)

Make sure you have Python installed on your system. You can install the required dependencies using the following:

pip install opencv-python

MATLAB

Ensure you have MATLAB installed on your machine. The code provided here is compatible with MATLAB R2018b and later versions.

Usage

1. Clone the repository:

git clone https://github.com/promit-3o20/DIP.git
cd DIP

2. Navigate to the specific task or algorithm folder.

3. Run the Python scripts using:

python script_name.py

For MATLAB scripts, open MATLAB and run the script by entering:

script_name

Examples

1. Image Filtering:

   • Apply various filters such as Gaussian, Median, and Sobel.

2. Image Enhancement:

   • Use techniques like histogram equalization and contrast stretching.

3. Object Detection:

   • Utilize OpenCV for object detection tasks using pre-trained models.

4. Image Segmentation:

   • Perform image segmentation using different algorithms.

5. Feature Extraction:

   • Extract features from images using OpenCV and MATLAB functions.

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

1. Fork the repository.
2. Create your feature branch: git checkout -b feature-name.
3. Commit your changes: git commit -m 'Add some feature'.
4. Push to the branch: git push origin feature-name.
5. Open a pull request.

License

This project is licensed under the MIT License.

---

Feel free to explore and adapt the code for your own image processing tasks. Happy coding!