학술논문

Design and Implementation of Lane Detection using Hough Transformation
Document Type
Conference
Source
2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) Applied Artificial Intelligence and Computing (ICAAIC), 2023 2nd International Conference on. :927-932 May, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Integrated optics
Machine learning algorithms
Lane detection
Transforms
Road safety
Real-time systems
Safety
Optical sensors
Vehicles
Accidents
Lanes
Lane Detection
Road
Driver-aid systems
Deep Learning
Hough Transform
Algorithm
etc
Language
Abstract
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.