TheDozMan / State-of-the-Art-Lane-Line-Detection

Reliable and consistent lane line detection for self driving cars across change of road conditions, lighting conditions, different coloured lane lines and surpassing vehicles

State-of-the-Art-Lane-Line-Detection

Content overview

• 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.