Image Processing Repository

This repository contains a collection of Jupyter Notebooks showcasing the basics of image processing and various techniques used in the field. The notebooks cover a range of topics, including functions, contour analysis, color detection, correlation theorem, feature extraction, Fourier transformation, and segmentation.

Table of Contents

1. Introduction to Image Processing: Provides an overview of image processing concepts, including image representation, pixel manipulation, and image transformation techniques.

2. Functions in Image Processing: Explores various functions used in image processing, such as image filtering, thresholding, and morphological operations.

3. Contour Analysis: Demonstrates contour detection and analysis techniques, including contour approximation, bounding boxes, and convex hulls.

4. Color Detection: Shows how to detect and extract specific colors from images using color spaces and thresholding techniques.

5. Correlation Theorem: Discusses the correlation theorem and its applications in image processing, including image filtering and template matching.

6. Feature Extraction: Covers feature extraction methods like Harris Corner Detection and SIFT (Scale-Invariant Feature Transform) for identifying and describing distinctive image features.

7. Fourier Transformation: Explores the Fourier transformation and its applications in image analysis, including frequency domain filtering and image reconstruction.

8. Image Segmentation: Focuses on image segmentation techniques, including thresholding, edge detection, and region-based segmentation algorithms.

Requirements

To run the notebooks, you will need the following dependencies:

• Python 3.x
• Jupyter Notebook
• OpenCV
• NumPy
• Matplotlib

It is recommended to set up a virtual environment and install the dependencies listed in the requirements.txt file before running the notebooks.

Getting Started

1. Clone this repository to your local machine using the following command:

   git clone https://github.com/your-username/image-processing-repo.git
   

2. Navigate to the cloned repository and install the required dependencies:

   pip install -r requirements.txt
   

3. Launch Jupyter Notebook:

   jupyter notebook
   

4. Open the desired notebook from the notebooks directory and run the cells to interact with the code and explore the image processing techniques.

Feel free to explore the notebooks and experiment with the code to gain a deeper understanding of image processing concepts and techniques.

License

This repository is licensed under the MIT License. You are free to use the code and modify it according to your needs.

Please refer to the individual notebook files for detailed explanations, code examples, and visualizations related to each image processing technique.

For any questions or feedback, feel free to reach out. email - [email protected]

Happy learning and exploring image processing techniques!