Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Crosswalk and Stop Line Recognition System for Autonomous Vehicles

무인 자율 주행 자동차를 위한 횡단보도 및 정지선 인식 시스템

  • 박태준 (한국기술교육대학교 컴퓨터공학부) ;
  • 조태훈 (한국기술교육대학교 컴퓨터공학부)
  • Received : 2010.12.28
  • Accepted : 2012.04.02
  • Published : 2012.04.25
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Abstract

Recently, development of technologies for autonomous vehicles has been actively carried out. This paper proposes a computer vision system to recognize lanes, crosswalks, and stop lines for autonomous vehicles. This vision system first recognizes lanes required for autonomous driving using the RANSAC algorithm and the Kalman filter, and changes the viewpoint from the perspective-angle view of the street to the top-view using the fact that the lanes are parallel. Then in the reconstructed top-view image this system recognizes a crosswalk based on its geometrical characteristics and searches for a stop line within a region of interest in front of the recognized crosswalk. Experimental results show excellent performance of the proposed vision system in recognizing lanes, crosswalks, and stop lines.

최근 무인 자율 주행 자동차를 실현하기 위한 기술 개발이 활발히 이루어지고 있는 추세이다. 본 논문에서는 무인 자율 주행 자동차의 핵심 기술인 컴퓨터 비전을 이용한 무인 자율 주행 자동차를 위한 횡단보도 및 정지선 인식 시스템을 제안한다. 본 논문의 컴퓨터 비전 시스템은 먼저 무인주행을 위하여 반드시 필요로 하는 차선을 RANSAC 알고리즘과 Kalman 필터를 이용하여 인식하고 인식된 차선이 실제로는 평행하다는 점을 이용하여 원근 시점인 입력 영상을 평면 시점으로 변환하여 횡단보도의 크기가 일정하게 만든다. 그런 후, 변환된 영상에서 횡단보도의 기하학적 특징을 이용하여 횡단보도를 인식하고 횡단보도 앞의 영역을 관심 영역으로 설정한 후 설정된 관심 영역에서 정지선을 추출한다. 구현된 알고리즘을 다양하게 실험한 결과 차선, 횡단보도, 정지선에 대하여 높은 인식률을 보였다.

Keywords

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