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Udacity Self-Driving Car Nanodegree - project #4 - Advanced Lane Finding

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Udacity Self-Driving Car Nanodegree

Project #4: Advanced Lane Finding

The goals of this project are to:

  • Build a software pipeline (pipeline.ipynb) to identify the driving lane in a video, including 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, 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.
  • Write a detailed report on the project (writeup.md)

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Udacity Self-Driving Car Nanodegree - project #4 - Advanced Lane Finding

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