Typically, road lanes are solid or dashed line formations that are continuous on the surface. As the driving sceneries are continuous as well as substantially overlap, the placement of lanes in one frame is highly correlated with their position in the next frame. Computer vision-related machine learning algorithms have also advanced rapidly in recent years, becoming both more efficient & more effective as high-precision optical and electronic sensors become more commonplace, and real-time driving scene recognition is becoming more feasible. Recent years have seen several technical breakthroughs in the field of road safety, as the number of accidents has risen at an alarming pace, with driver inattention being one of the primary causes. To minimize the incidence of accidents as well as maintain safety, technological advances are required. Lane Detection Systems, which operate to recognize the lane boundaries on the road as well as alert the driver if he changes and goes to incorrect lane markings, are one method of achieving this goal. A lane detection system is a crucial element of many technologically advanced transportation systems. This research uses the Hough Transform technique for lane identification.
Design and Implementation of Lane Detection using Hough Transformation
2023-05-04
822387 byte
Conference paper
Electronic Resource
English
Road Lane Line Detection Based on ROI Using Hough Transform Algorithm
Springer Verlag | 2022
|A NEW APPROACH TO HIGHWAY LANE DETECTION BY USING HOUGH TRANSFORM TECHNIQUE
DOAJ | 2017
|A Review of Multiple Edge Detection in Road Lane Detection Using Improved Hough Transform
Trans Tech Publications | 2015
|Underwater vehicle attitude estimation using Hough transformation
British Library Conference Proceedings | 2008
|