Graph Model-Based Lane-Marking Feature Extraction for Lane Detection
This paper presents a robust, efficient lane-marking feature extraction method using a graph model-based approach. To extract the features, the proposed hat filter with adaptive sizes is first applied to each row of an input image and local maximum values are extracted from the filter response. The...
Main Authors: | Juhan Yoo, Donghwan Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/13/4428 |
Similar Items
-
Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data
by: Justin A. Mahlberg, et al.
Published: (2021-09-01) -
Interactive Attention Learning on Detection of Lane and Lane Marking on the Road by Monocular Camera Image
by: Wei Tian, et al.
Published: (2023-07-01) -
PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads
by: Wen-Chang Cheng
Published: (2012-12-01) -
Lane Departure Assessment via Enhanced Single Lane-Marking
by: Yiwei Luo, et al.
Published: (2022-03-01) -
Lane Detection Method with Impulse Radio Ultra-Wideband Radar and Metal Lane Reflectors
by: Dae-Hyun Kim
Published: (2020-01-01)