This repository showcases a suite of five desktop applications built from scratch to demonstrate fundamental image processing and computer vision algorithms.
Each application provides an interactive and visual understanding of how classic CV algorithms work — from basic filtering to object detection — through intuitive GUIs.
| Application | Description |
|---|---|
| 1. Image Enhancement and Processing Lab | Apply spatial and frequency domain filters (Gaussian, Median, Sobel, etc.). Histogram operations like equalization. Different Edge detection algorithms |
| 2. Edge and Boundery Detection Lab | Experiment with edge detectors like Canny, Hough Transform, and SNAKE Contour Model. |
| 3. Feature Extraction & Matching | Implements Harris corner, SIFT, and different feature matching functions. |
| 4. Image Thresholding & Segmentation Tool | Implements different thresholding and segmentation algorithms with paramters control. |
| 5. Eign Faces | Face Detection and Recognition using eign analysis. |
- Python 3.x
- PyQt5 – for desktop GUI
- OpenCV – for image processing algorithms
- NumPy – for numerical computations
- Matplotlib / PyQtGraph – for visualization
 Fatma Elsharkawy |
 Hajer Ehab |
 Judy Ashmawy |
 Laila Khaled |