Image Processing Labs

This project contains a series of Jupyter notebooks and Python scripts that demonstrate the use of Fourier Transform for image analysis. Each lab focuses on different aspects of Fourier Transform and image processing techniques.

Project Structure

• lab1/ - Contains the first lab notebook focusing on image contrast correction and histogram visualization.
• lab2/ - Contains the second lab notebook which covers image noise analysis and filtering techniques.
• lab3/ - Contains the third lab notebook and a ressources.py script. This lab introduces Fourier Transform analysis with functions such as fourier2d_all, fourier2d_single_frenquency, fourier2d_many_frequencies, and fourier2d_vue3d_old.
• lab4/ - Contains the fourth lab notebook which delves into image segmentation techniques.
• lab5/ - Contains the fifth lab notebook focusing on image segmentaation using Region Growing Algorithm

Each lab folder also contains a resources/ directory with images and other files used in the lab exercises.

Prerequisites

• Python 3.10 or higher
• pip

Installation

1. Clone this repository to your local machine.

   git clone https://github.com/Hamza-cpp/img-processing-labs

2. Navigate to the project directory.

   cd ./path/to/img-processing-labs

3. Create and activate the virtual env:

   python -m venv .venv && source .venv/bin/activate

4. Install the necessary dependencies using pip:

   pip install -U pip
   pip install -r requirements.txt

Running the Notebooks

To run the notebooks, you need to have Jupyter installed. If not, you can install it with:

pip install jupyter

Then, you can start Jupyter by running:

jupyter notebook

This will open a web browser where you can navigate to the notebook files .ipynb and open them.

Contributing

Contributions are welcome. Please open an issue to discuss your idea or submit a Pull Request.