Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Lane Tracking Algorithm Using IPM and Kalman Filter

역투영 변환과 칼만 필터를 이용한 주행차선 추적

  • Yeo, Jae-Yun (Department of Electrical and Computer Engineering, Pusan National University) ;
  • Koo, Kyung-Mo (Department of Electrical and Computer Engineering, Pusan National University) ;
  • Cha, Eui-Young (Department of Electrical and Computer Engineering, Pusan National University)
  • Received : 2013.10.01
  • Accepted : 2013.11.06
  • Published : 2013.11.30
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Abstract

In this paper, A lane tracking algoritm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Using clustering and lane similarity function with noise suppression features are extracted. Finally, lane model is calculated using RANSAC and lane model is tracked using Kalman Filter. Experimental results show that the proposed algorithm can be processed within 20ms and its detection rate approximately 90% on the highway in a variety of environments.

본 논문에서는 차선 이탈 경고 장치 시스템에서 사용될 수 있는 주행차선 추적 방법을 제안한다. 먼저 역투영 변환을 이용해 차량에 부착된 카메라로 입력 받은 영상의 원근 효과가 제거된 조감도 영상을 생성한다. 그다음 차선의 형태학적 사전 지식을 이용하여 차선 검출에 적합한 특징들을 추출한다. 이후 블록 단위의 관심영역에 해당하는 차선 특징을 클러스터링하고 차선 유사도 함수를 이용함으로써 잡음이 제거된 차선 특징들을 얻을 수 있다. 이후 RANSAC(RANdom Sample Consensus) 알고리즘을 사용하여 차선 모델을 계산하고 칼만 필터를 이용하여 검출된 차선 모델을 추적한다. 제안하는 알고리즘은 고속도로 상의 다양한 환경에서 20ms 이내의 처리 속도와 90% 가량의 추적률을 얻을 수 있었다.

Keywords

References

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Cited by

  1. Recognition of Lanes, Stop Lines and Speed Bumps using Top-view Images vol.65, pp.11, 2016, https://doi.org/10.5370/KIEE.2016.65.11.1879