A manual implementation of the Hough transform to aid in the task of road lane detection.

This project was developed as part of the course Computer Vision in the Fall 2022 semester at the Faculty of Engineering, Alexandria University, under the Computer and Communications Engineering department, supervised by Dr. Marwan Torki.

1- Smoothing the image using a 2-dimensional median smoothing filter.

2- Edge Detection using Canny’s algorithm.

3- Region Of Interest selection.

4- Accumulation into (ρ, θ)-space using Hough transform.

This project was developed in the following environment:

• Jupyter Notebook
• Miniconda
• Python 3.11.5

1- Clone the repository to your local machine:

git clone https://github.com/MohEsmail143/road-lane-detection.git

2- Open Jupyter notebook.

3- Check out the the Jupyter notebook road_lane_detection.ipynb.

This project is licensed under the MIT License - see the LICENSE.md file for details.