Advanced-Lane-Detection
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Project: Advanced Lane Finding || Udacity: Self-Driving Car Engineer Nanodegree
Advanced Lane Detection
Udacity Self-Driving Cars ( Nanodegree )
This repository contains the code that can detect lane lines on the road. Advanced computer vision techniques are used in this 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.
Written in C++ with OpenCV library