There are 2 repositories under detect-lane-lines topic.
Udacity Self-Driving Car Engineer Nanodegree projects.
Lane Finding Project for Self-Driving Car Nano Degree Term 1. Road Lane Lines are detected by using various image processing techniques like Grayscale, Blurring, Canny Edge Detection, Hough Transform and Masking.
A lane detection pipeline by tracking white and yellow colored lane lines using self adjusting Canny edge detector implemented in HSL color space to make it intensity invariant.
Contains sub-modules of self-driving algorithms
Lane detection for autonomous navigation using opencv library, done as a part of Udacity Self Driving Car Nanodegree Program
Detecting lane lines using canny edge detection and hough transformation
This repository contains my development of the Project: Advanced Lane Lines proposed by the Udacity's Self-Driving Cars Nanodegree
Detecting Lanes for Self-Driving-Cars... I have developed a software pipeline to identify the lane boundaries in a video from a front-facing camera on a car
Advanced lane line detection using perspective transformation and gradient and color image thresholding - implemented as part of the Udacity Self Driving Car NanoDegree
Udacity Self Driving Car Engineer Nanodegree projects
Self-Driving Car Nanodegree
Project 1 Term 1 - Find lane lines
CarND lane lines detection with opencv
Lane Finding Project for Self-Driving Car
Lane lines detection using OpenCV, UDACITY Self-driving Car Engineer Nanodegree program
This repository contains my development of the Project: Finding Lane Lines proposed by the Udacity's Self-Driving Cars Nanodegree
The first project in the Udacity Self-Driving Car Nanodegree is about implementing a pipeline that detects lane lines in images. While the pipeline is created for a single image, it can be applied to video footage by breaking the video down into frames, passing the frames through the pipeline, and then reconstructing the video.
This repository contains a collection of projects focused on the development of self-driving car technology. The work demonstrates practical applications of key concepts in autonomous systems.
Lane Detection for self driving cars
Lane Finding Project for Self-Driving Car Nano Degree Term 1. Road Lane Lines are detected by using various image processing techniques like Grayscale, Blurring, Canny Edge Detection, Hough Transform and Masking.
This is the first project from Udacity Self-Driving Car Nanodegree.
My notebook for the Udacity finding lane lines project
Udacity CarND - Project 01 - Lane Lines