Hough Transform for Line Detection

This repository provides a detailed guide and implementation from scratch of the Hough Transform algorithm for line detection in Python using OpenCV. The Hough Transform is a powerful tool in computer vision for feature extraction, particularly in scenarios where detecting lines is crucial, such as lane detection in autonomous vehicles.

About the Hough Transform

The Hough Transform is a widely used algorithm in computer vision that enables the detection of lines, circles, ellipses, and other shapes in images. In this repository, we focus specifically on the implementation of the Hough Transform for detecting lines.

Contents

• Implementation Guide: Step-by-step instructions for implementing the Hough Transform from scratch using Python and OpenCV.
• Code: Python scripts containing the implementation of the Hough Transform algorithm, along with examples and usage instructions.
• Examples: Example images and datasets for testing the Hough Transform implementation.

Getting Started

To get started with using the Hough Transform for line detection, simply clone this repository to your local machine and run the notebook using Jupyter notebook.

Dependencies

• Python 3.x
• OpenCV
• NumPy
• Matplotlib

Usage

Clone the repository to your local machine:

git clone https://github.com/yourusername/hough-transform.git

And then run it with Jupyter notebook!

License

This repository is licensed under the MIT License. See the LICENSE file for more details.