Computer Vision Portfolio

Welcome to my comprehensive repository showcasing advanced implementations in Computer Vision

Computer Vision & Image Processing

A deep dive into visual data manipulation using OpenCV, from basic pixel operations to object detection.

📁 Image Foundations & Spatial Operations

• Preprocessing: Histogram Equalization for contrast and Image Pyramids for multi-scale analysis.
• Boundary Management: Implementation of various Border types (Replicate, Reflect) for convolution.
• Thresholding: Global and Adaptive techniques for image binarization.

[Image of Image Histogram Equalization: Before and After]

📁 Feature Engineering & Detection

• Edge & Corner Detection: Implementing Sobel, Canny, and Harris Corner detection.
• Geometric Shapes: Using the Hough Line Transform and Circle Detection.

[Image of Canny Edge Detection process: Noise reduction, Gradient calculation, Non-maximum suppression]

📁 Advanced Segmentation & Detection

• Color Filtering: Real-time object isolation using HSV Color Masks.
• Object Detection: Face and eye detection using Haar Cascade Classifiers.
• Clustering: Image segmentation using K-Means and Agglomerative clustering.

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🛠️ Technical Stack

• Languages: Python 3.x
• Core Libraries: OpenCV, Scikit-Learn, NumPy, Pandas, Matplotlib
• Environments: Jupyter Notebooks, Streamlit Cloud.

👨‍💻 Author

Mostafa Mahmoud Computer Science & Data Science Student linked-in : https://www.linkedin.com/in/mostafa-hamad-4914292a8/