The goals / steps of this project are the following:
- 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, etc., 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.
The program of this project is mainy constructed on:
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OpenCV
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Numpy
These technics are employed in this project:
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Camera calibration and image undistortion
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Line detection by sobel computation and HSL channel filtering
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Perspective transformation
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Line fitting
The images for camera calibration are stored in the folder called camera_cal. The images in test_images are for testing your pipeline on single frames.
The output from each stage of my pipeline are in the folder called output_images. The video called project_video.mp4 is the video my pipeline finally work on.
A description of the technichs, the pipeline, and the discussion of this project is written in writeup.md