Note: this is Udacity Nano Degree project, This project was forked from Udacity
In this project, I did the following steps:
- Compute the camera calibration matrix and distortion coefficients given a set of chessboard images.
- Apply a distortion correction to raw images.
- Use color transforms, gradients to create a thresholded binary image.
- Apply a perspective transform to rectify binary image ("birds-eye view").
- Detect lane pixels and fit to find the lane boundary.
- Determine the curvature of the lane and vehicle position with respect to center.
- Warp the detected lane boundaries back onto the original image.
- Output visual display of the lane boundaries and numerical estimation of lane curvature and vehicle position.
Here is the result video:
- Project wirteup report in Writeup_report
- Code in Advanced_Lane_Finding
- Example output images in output_images