JICCE (한국정보통신학회)
Current Result Document :
| 한글제목(Korean Title) |
Real Time Road Lane Detection with RANSAC and HSV Color Transformation |
| 영문제목(English Title) |
Real Time Road Lane Detection with RANSAC and HSV Color Transformation |
| 저자(Author) |
Kwang Baek Kim
Doo Heon Song
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| 원문수록처(Citation) |
VOL 15 NO. 03 PP. 0187 ~ 0192 (2017. 09) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Autonomous driving vehicle research demands complex road and lane understanding such as lane departure warning, adaptive cruise control, lane keeping and centering, lane change and turn assist, and driving under complex road conditions. A fast and robust road lane detection subsystem is a basic but important building block for this type of research. In this paper, we propose a method that performs road lane detection from black box input. The proposed system applies Random Sample Consensus to find the best model of road lanes passing through divided regions of the input image under HSV color model. HSV color model is chosen since it explicitly separates chromaticity and luminosity and the narrower hue distribution greatly assists in later segmentation of the frames by limiting color saturation. The implemented method was successful in lane detection on real world on-board testing, exhibiting 86.21% accuracy with 4.3% standard deviation in real time.
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| 키워드(Keyword) |
Autonomous driving
Bezier spline
HSV
RANSAC
Road lane detection
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| 파일첨부 |
PDF 다운로드
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