Lane Detection Using Hough Transform for Straight Line Identification
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
In this paper, we demonstrate how to utilize Hough transform for lane straight-line detection. This algorithm represents a highly effective approach applicable to lane detection on road surfaces captured by imaging systems. The implementation typically involves preprocessing steps such as converting images to grayscale and applying Gaussian blur before edge detection using operators like Canny. Through feature extraction from images, we identify lane markers and convert them into linear equations using Hough line detection functions (e.g., cv2.HoughLinesP in OpenCV). The process includes transforming edge points from Cartesian coordinates to Hough parameter space, where peak detection identifies dominant lines. This methodology enables precise determination of vehicle positioning on roadways, thereby enhancing both safety and measurement accuracy through robust line fitting and outlier rejection mechanisms.
- Login to Download
- 1 Credits