Advanced Lane Finding (project 2 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
-
Updated
May 24, 2020 - Python
Advanced Lane Finding (project 2 of 9 from Udacity Self-Driving Car Engineer Nanodegree)
GIMP3 plugin for correcting Chromatic Aberration (CA)
Identify the lane boundaries in a video from a front-facing camera on a car
A python library for image stitching with distortion correction
Images and notebook for camera calibration
Udacity Self Driving Engineer Nanodegree - Project 4 - Advanced Lane Finding
Advanced Lane Tracking Project - uses perspective transforms to track lane position
In this project, a software pipeline was written to identify the lane boundaries in a video from a front-facing camera on a car using computer vision techniques with openCV.
SW Pipeline to identify the lane boundaries from a front-facing camera on a car (use of OpenCV)
Goal is to create a software pipeline to identify the lane boundaries in a video and write a detailed commentary on the output.
In this project, I have used computer vision techniques to identify lane boundaries and compute the lane metrics (radius of curvature, Offset to the center).
Computer Vision Algorithms
Udacity Self Driving Car Nanodegree - Advanced Lane Finding
Applied signal processing to dash-cam video feed to detect lane lines on the road and used numerical methods to derive approximate real-world measurements of the lane lines.
Advance Lane Line Finder on a Video Stream
Advanced lane line fining including camera calibration
Camera Calibration and Distortion Correction
A cv2-based implementation of a self-driving car module responsible for lane lines detection under different lighting conditions, pavement textures and curves.
Add a description, image, and links to the distortion-correction topic page so that developers can more easily learn about it.
To associate your repository with the distortion-correction topic, visit your repo's landing page and select "manage topics."