A structured collection of Image Processing tutorials implemented in Python using Jupyter Notebooks.
The repository is organized as a step-by-step learning series, covering both fundamental concepts and practical applications.
This repository is intended for:
- Image Processing coursework
- Learning computer vision fundamentals
- Practicing key algorithms through notebooks
- Image I/O and Color Spaces
- Histograms and Contrast Enhancement
- Convolution, Kernels, and Filtering
- Noise Reduction Techniques
- Frequency Domain Processing
- Thresholding and Morphological Operations
- Edge and Contour Detection
- Segmentation and Connected Components
- Geometric Transformations
Each notebook is self-contained and focuses on a specific concept with examples and exercises.