CSE428 - Image Processing

Academic resources and materials for Image Processing coursework at BRAC University

Course Overview

This repository serves as a comprehensive archive of course materials, laboratory exercises, assignments, and academic resources for CSE428: Image Processing. The course covers fundamental concepts of digital image processing ranging from basic pixel manipulation to advanced deep learning techniques for computer vision, including mathematical foundations and practical algorithms used to manipulate digital images.

Key Topics

• Digital Image Fundamentals: Sampling, quantization, and color models
• Image Enhancement: Spatial and frequency domain filtering, histogram processing
• Image Segmentation: Edge detection, thresholding, and region-based segmentation
• Machine Learning Integration: Neural Networks, CNNs, and U-Net architectures for advanced classification and segmentation

Course Project

The main course project is hosted in a separate repository for better organization and collaboration:

Project Repository: NeuroSeg-Classification

This project focuses on brain tumor image segmentation and classification using advanced image processing and machine learning techniques.

Tools and Technologies

• Python - Primary programming language
• OpenCV - Computer vision library
• NumPy - Numerical computing
• Matplotlib - Visualization
• scikit-image - Image processing algorithms
• PyTorch/TensorFlow - Deep learning frameworks

Getting Started

Clone this repository to access lab materials and resources:

git clone https://github.com/fah-ayon/CSE428.git
cd CSE428

Academic Integrity

This repository is intended for educational purposes. Please adhere to your institution's academic integrity policies when using these materials.

License

This repository contains academic coursework. All rights reserved for educational use.

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Author

Abdullah Al Fahad

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