교통영상에서의 규칙에 기반한 차량영역 검출기법

Rule-based Detection of Vehicles in Traffic Scenes

  • 박영태 (경희대학교 전자정보학과)
  • Park, Young-Tae (School of Electronics & Information Kyung Hee University)
  • 발행 : 2000.05.25

초록

영상정보에 기반한 교통제어시스템의 핵심요소인 교통영상에서의 차량의 위치, 대수를 측정하는 견실한 기법을 제시하였다. 제안한 기법은, 배경영상을 제거한 차 영상으로부터 국부 최적 임계값 산출기법에 의해 차량의 밝고 어두운 증거영역을 추출하고 차량의 기하학적 특정을 이용해 3개의 규칙으로 합병하는 증거추론 (Evidential reasoning)에 기반을 두었다 국부 최적 임계값 산출기법은 차량형상이 중첩되었거나 차량의 색상이 배경영상과 유사할 경우에도 치량의 밝고 어두운 증거영역의 분리를 보장한다 다양한 교통영상에 적용한 결과 카메라의 거리, 위치, 날씨 등의 동작 환경의 변화에 매우 견실한 검지 성능을 가점을 확인하였고 프레임사이의 움직임 정보를 사용하지 않았으므로 차량의 흐름이 정체되었을 경우에도 적용이 가능하다.

A robust scheme of locating and counting the number of vehicles m urban traffic scenes, a core component of vision-based traffic monitoring systems, is presented The method is based on the evidential reasoning, where vehicle evidences m the background subtraction Image are obtained by a new locally optimum thresholding, and the evidences are merged by three heuristic rules using the geometric constraints The locally optimum thresholding guarantees the separation of bright and dark evidences of vehicles even when the vehicles are overlapped or when the vehicles have similar color to the background Experimental results on diverse traffic scenes show that the detection performance is very robust to the operating conditions such as the camera location and the weather The method may be applied even when vehicle movement is not observed since a static Image IS processed without the use of frame difference.

키워드

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