The goal of this project is to write a software pipeline to identify the lane boundaries in a video.
The pipeline uses standard computer vision techniques to correct distortion in the video, perform perspective transformations to get a bird's eye view of the lane. Then, Sobel edge detection is combined with color thresholding, to identify which pixels belong to the lane lines. A polynomial equation is fit to these lines and a polygon is drawn to cover the lane. Finally, the image is warped back to its original perspective.
Check out my writeup to learn more about my process and how it works.
This lab requires:
The images for camera calibration are stored in the folder called camera_cal. The images in test_images are for testing the pipeline on single frames. The output from each stage of the pipeline is in the folder called output_images.
The challenge_video.mp4 video is an extra (and optional) challenge for testing the pipeline under somewhat trickier conditions. The harder_challenge.mp4 video is another optional challenge and is even harder.
The result of running the pipeline on project_video.mp4 can be seen in output_video.mp4.