논문 국내 국내전문학술지(KCI급) 가우시안 혼합모델을 이용한 강인한 실시간 곡선차선 검출 알고리즘
- 학술지 구분 국내전문학술지(KCI급)
- 게재년월 2016-01
- 저자명 장찬희, 이순주, 최창범, 김영근
- 학술지명 제어.로봇.시스템학회 논문지
- 발행처명 제어.로봇.시스템학회
- 발행국가 국내
- 논문언어 한국어
- 전체저자수 4
- 연구분야 공학 > 제어계측공학
- 원문 링크 https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=JAKO201620049013230&SITE=CLICK
홈페이지논문 초록 (Abstract)
ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.