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Advanced Lane Finding (project 2 of 9 from Udacity Self-Driving Car Engineer Nanodegree)

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Advanced Lane Finding

Udacity - Self-Driving Car NanoDegree Lanes Image In this project, my goal is to write a software pipeline to identify the lane boundaries in a video from a front-facing camera on a car.

The Project

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 images for camera calibration are stored in the folder called camera_cal. The images in test_images are for testing my pipeline on single frames.