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In this project, I have used computer vision techniques to identify lane boundaries and compute the lane metrics (radius of curvature, Offset to the center).

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SABKI/Advanced-line-lane-detection

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Advanced Lane Finding

Udacity - Self-Driving Car NanoDegree

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.

Please refer to the writeup pdf (Advanced Lane Finding_WRITEUP.pdf) for much details about this project.

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In this project, I have used computer vision techniques to identify lane boundaries and compute the lane metrics (radius of curvature, Offset to the center).

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