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

  • 제8권3호
  • /
  • Pages.708-713
  • /
  • 2004
  • /
  • 2234-4772(pISSN)
  • /
  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
권호 표지

영상분할을 이용한 효율적인 주차검출

An Efficient Vehicle Parking Detection Method Using Image Segmentation

  • 발행 : 2004.06.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

그레이 스케일 이미지를 이용한 차량 감지 방법은 주차장에서 빈 공간으로 진입하는 차량의 안내나 기타 유사한 목적들을 위해 제안되고 있다. 본 논문은 그레이레벨 이미지를 이용하여 주차여부를 확인하고, 주차공간을 분석하는 방법을 제안한다. 실험결과로써 각기 2일 동안 새벽부터 해질녘까지 야외 주차장을 이용하여 획득한 129개의 영상을 이용하여 실험한 결과 98.7％의 성공률을 나타내었다.

A method of individual vehicle detection using gray scale image acquired from a high position is proposed for guidance of incoming vehicles to vacant cells in a parking lot and other similar purposes. With the proposed method, each image region corresponding to a cell is fragmented according to density(gray level), and the distribution of segment area is analyzed to decide if a vehicle is present. The proposed method was tested on an actual outdoor parking lot during 2 days with different weather conditions from sunrise through sunset.

키워드

참고문헌

  1. Koizumi M, Koyama S. 'Parking lot monito-hng system based on image processing in Tomei Expressway', Kosokudoroto Jidosha 1992;35:32-40
  2. Takahashi Y et al. 'Image recognition tech-nology for automation of parking lot management', NTT R&D 1992;41:493-500.
  3. Maeda E et al. 'Object detection method with robustness to environmental changes', Trans IEICE 1991;J74-D-II:1731-1740
  4. Maeda E, Ishii K. 'Evaluation of prindpal component feature characteristics in object detection', Trans IEICE 1991;J75-D-II:520-529
  5. Mizukoshi N et al. 'Parking condition discrimination system of image processing type using a neural network model', IEEE Vehicle Navigation & Information Systems Conf, p 69-74, 1994
  6. Miyake M et al. 'Nighttime detection of vehicles in parking lot using image processing' Road Traffic Committee of IEE Japan, RTA-91-23, 1991
  7. Hasegawa T et al. Counting cars by tracking moving objects in outdoor parkinglot. IEEE Vehicle Navigation and Information Systems Conf, p 63-68, 1994
  8. Sakaida, Shinichi, Naemura, Masahide, Kanatsugu, 'Moving object extracdon using background difference and region growing with a spatio- temporal watershed algorithm' Systems and computers in Japan, v.33 no.12/ p 11-26, 2002 https://doi.org/10.1002/scj.10237
  9. Betke, Margrit, Hahtaoglu, Esin, Davis, Larry S. 'Real-time multiple vehicle detection and tracking from a moving vehicle', Machine vision and applications, v.12 no.2, pp.69-83, 2000 https://doi.org/10.1007/s001380050126