Extracting Real-Time Traffic Information By Spatio-Temporal Image Analysis

시공간 영상분석에 의한 실시간 교통정보 산출기법

  • Lee, Young-Jae (School of Electronics & Information Kyung Hee University) ;
  • Lee, Dae-Ho (School of Electronics & Information Kyung Hee University) ;
  • Park, Young-Tae (School of Electronics & Information Kyung Hee University)
  • 이영재 (경희대학교 전자정보공학부) ;
  • 이대호 (경희대학교 전자정보공학부) ;
  • 박영태 (경희대학교 전자정보공학부)
  • Published : 2000.07.25

Abstract

Real-time extraction of traffic information such as the number of vehicles passing, speed, road-occupancy rate, distance between vehicles, and vehicle types from the traffic scenes acquired from the camera on the road, is a core component of the intelligent transportation system(lTS) We present a scheme of extracting the traffic informations based on the spatio-temporal image analysis, which is robust to the variation of weather conditions and the shades. The images of two detection regions for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shade, using the statistical and structural features Quantitative traffic informations are retrieved by analysing the two spatio-temporal images. Since only the local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized while ensuring the detection performance robust to the operating condition.

도로 위에 설치된 카메라에서 획득한 입력 영상으로부터 각 차선의 통과 차량수, 차량속도 도로 점유율, 차간 거리, 차종 등의 교통정보를 실시간으로 산출하는 기법은 지능형 교통 시스템(ITS)의 핵심 분야이다. 본 논문에서는 검지영역의 시공간 영상 분석에 의해 다양한 기상 조건과 그림자 등의 환경의 변화에 민감하지 않은 교통정보 산출기법을 제안한다. 각 차선에 2개의 검지영역을 설정하고 검지영역의 통계적 특성과 형상적 특성을 이용해 도로영역, 그림자 영역, 차량영역으로 분류하여 차량을 검지하며 시공간 영상 분석을 통하여 정량적 교통정보를 산출한다. 제안한 기법은 영상의 국부 검지영역 데이터만을 사용하므로 1초에 30 프레임이상의 실시간 처리가 가능하며 기상 조건과 그림자의 변화에 견실한 차량검지 및 교통정보 산출 능력을 구현할 수 있다.

Keywords

References

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