A Computer Vision desktop application developed using C++, Qt, and OpenCV that demonstrates multiple classical image processing and segmentation algorithms implemented mostly from scratch.
The application provides an interactive GUI where users can load images, apply different thresholding and segmentation techniques, and visualize the results in real time.
This project focuses on implementing and comparing several fundamental Computer Vision algorithms used in:
- 🖼️ Image Thresholding
- ✂️ Image Segmentation
- 📊 Clustering
- 🌱 Region-Based Processing
- 🎯 Feature Space Analysis
The application is designed as both:
- 📚 An educational tool
- 🛠️ A practical image processing application
- Optimal Thresholding
- Otsu Thresholding
- Spectral Thresholding
- Local Adaptive Thresholding
- K-Means Clustering
- Region Growing
- Agglomerative Clustering
- Mean Shift Segmentation
- Interactive Qt-based interface
- Dynamic parameter controls
- Real-time visualization
- Input/Output image comparison
- Modern dark theme UI
- 💻 C++
- 🎨 Qt Framework
- 👁️ OpenCV
- 📈 Computer Vision Algorithms
- 🧮 Image Processing
- 🤖 Clustering Algorithms
project/
│
├── main.cpp
├── mainwindow.h
├── mainwindow.cpp
├── README.md
├── resources/
│ └── sample_images/
│
└── build/