Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Real-Time Lane Detection Based on Inverse Perspective Transform and Search Range Prediction

역 원근 변환과 검색 영역 예측에 의한 실시간 차선 인식

  • Jeong, Seung-Gweon (Dept.of Intelligent Mechanical Engineering, Busan National University) ;
  • Kim, In-Soo (Dept.of Intelligent Mechanical Engineering, Busan National University) ;
  • Kim, Sung-Han (Dept.of Intelligent Mechanical Engineering, Busan National University) ;
  • Lee, Dong-Hwoal (Dept.of Intelligent Mechanical Engineering, Busan National University) ;
  • Yun, Kang-Sup (Dept.of Automotive Industry Mechanical Engineering, Daegu University) ;
  • Lee, Man-Hyung (Dept.of Intelligent Mechanical Engineering, Busan National University)
  • 정승권 (부산대학교 지능기계공학과) ;
  • 김인수 (부산대학교 지능기계공학과) ;
  • 김성한 (부산대학교 지능기계공학과) ;
  • 이동활 (부산대학교 지능기계공학과) ;
  • 윤강섭 (대구대학교 자동차.산업.기계공학부) ;
  • 이만형 (부산대학교 기계공학부)
  • Published : 2001.03.01
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Abstract

A lane detection based on a road model or feature all needs correct acquirement of information on the lane in an image. It is inefficient to implement a lane detection algorithm through the full range of an image when it is applied to a real road in real time because of the calculating time. This paper defines two (other proper terms including"modes") for detecting lanes on a road. First is searching mode that is searching the lane without any prior information of a road. Second is recognition mode, which is able to reduce the size and change the position of a searching range by predicting the position of a lane through the acquired information in a previous frame. It allows to extract accurately and efficiently the edge candidate points of a lane without any unnecessary searching. By means of inverse perspective transform which removes the perspective effect on the edge candidate points, we transform the edge candidate information in the Image Coordinate System(ICS) into the plan-view image in the World Coordinate System(WCS). We define a linear approximation filter and remove faulty edge candidate points by using it. This paper aims at approximating more correctly the lane of an actual road by applying the least-mean square method with the fault-removed edge information for curve fitting.e fitting.

Keywords

References

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