Welcome to my Computer Vision Projects Portfolio! This repository showcases a collection of projects demonstrating various computer vision techniques and algorithms. Each project focuses on different aspects of image processing and analysis, providing a comprehensive overview of my skills and knowledge in the field.

This project implements the Canny edge detection algorithm along with additional image processing techniques like the Hough transform.

Key Features:

• Canny edge detection algorithm
• Gaussian smoothing
• Gradient calculation
• Non-maximum suppression
• Double thresholding
• Edge tracking by hysteresis
• Hough transform for line detection

A collection of Python functions for basic image processing operations, focusing on convolution and cross-correlation techniques.

Key Features:

• Naive and optimized 2D convolution implementations
• Zero-padding for images
• Zero-mean cross-correlation

This project implements facial detection and analysis using computer vision techniques, including HOG feature extraction and sliding window detection.

Key Features:

• HOG feature extraction from facial images
• Sliding window detection for face localization
• Image pyramid implementation for multi-scale detection
• Visualization tools for displaying results

An implementation of a panorama image stitching algorithm using various computer vision techniques.

Key Features:

• Harris corner detection
• Feature description (Simple descriptor and HOG)
• Feature matching
• RANSAC for robust estimation of affine transformation
• Image warping and blending

This project focuses on optical flow and feature tracking algorithms, primarily the Lucas-Kanade method and its variations.

Key Features:

• Lucas-Kanade optical flow algorithm
• Iterative and pyramidal Lucas-Kanade methods
• Feature detection using Harris corner detector
• Feature tracking across multiple frames
• Simple object tracking implementation

• Python
• NumPy
• scikit-image
• Matplotlib
• SciPy
• IPython (for some visualizations)

If you have any questions about these projects or would like to discuss potential opportunities, please feel free to contact me at [Your Email Address].

Thank you for visiting my Computer Vision Projects Portfolio!