Advanced lane detection using computer vision

detect curved lane lines using HSV filtering and sliding window search.

Lane detection and classification in an end-to-end Deep Learning fashion

Project: Advanced Lane Finding || Udacity: Self-Driving Car Engineer Nanodegree

Udacity Self-Driving Car Engineer.

This project is to detect lanes in a video or image and project the results on the output. advanced math and image processing including openCV was used to finish the project.

Finding lane lines on the road

Lane Marking Quality Assessment for Autonomous Driving

Detected highway lane boundaries on a video stream with OpenCV image analysis techniques, including camera calibration matrix, distortion correction, color transforms, gradients, etc., to create a thresholded binary image, a perspective transform to rectify binary image ("birds-eye view"). Detected lane pixels and fit to find the lane boundary, …

My Submission for Udacity Self Driving Car Nano Degree Advanced Lane Lines Project

Distinguish lanes for self-driving cars- using color selection, region masking & edge detection

This project utilizes a software pipeline to identify the lane boundaries in a video.

Advanced computer vision techniques to identify lanes, the position of the vehicle within the lane, the radius of curvature of the lane.

An OpenCV implementation of road lane detection written in Python.

Self-Driving Nano Degree Program : Advanced Lane Detection

C++ Lane Detection using OpenCV

Lane Detection for Self-Driving Cars

Advanced lane line fining including camera calibration

Finding Lane Lines on the Road (project 1 of 9 from Udacity Self-Driving Car Engineer Nanodegree)

Identify lane boundaries in a video and display numerical estimation of lane curvature and vehicle position using camera calibration and perspective transform ("birds-eye view").