Detected highway lane lines on a video stream. Used OpencV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection.
-
Updated
Dec 13, 2016 - Jupyter Notebook
Detected highway lane lines on a video stream. Used OpencV image analysis techniques to identify lines, including Hough Transforms and Canny edge detection.
Finding lane lines in images and videos using computer vision.
Curved Lane Detection by computer vision techniques such as perspective transform or image thresholding.
Identify the lane boundaries in a video from a front-facing camera on a car
Fourth Project of the Udacity Self-Driving Car Nanodegree Program
Developed a pipeline to process a video stream from a forward-facing camera mounted on the front of a car, and output an annotated video with position of lane lines and so on.
Find lane from camera images of an autonomus car
Apply computer vision to label the lanes in a driving video
Built an advanced lane-finding algorithm using distortion correction, image rectification, color transforms, and gradient thresholding. Identified lane curvature and vehicle displacement. Overcame environmental challenges such as shadows and pavement changes.
P4-Advanced-Lane-Finding
Detect lane lines on a road using computer vision techniques
Using OpenCV to Detect Road Lanes and Stabilize Results
A Lane finding pipeline implemented in Python and OpenCV based on gradient and colour thresholding
Identify the lane boundaries in a video.
Finding lanes boundaries and curvature of the road
Threshold an image interactively (HSV,HSL, Sobel X/Y)
Advanced lane detection (incl. curvature) using advanced computer vision techniques.
Udacity Self Driving Car Projects
Add a description, image, and links to the lane-finding topic page so that developers can more easily learn about it.
To associate your repository with the lane-finding topic, visit your repo's landing page and select "manage topics."