차선의 회전 방향 인식을 위한 신경회로망 응용 화상처리

Detection of Lane Curve Direction by Using Image Processing Based on Neural Network

  • 발행 : 1999.06.01

초록

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

키워드

참고문헌

  1. 추돌경보장치 개발에 관한 연구 김경주
  2. 日野技報 no.44 自動車用車間距離警報裝置 Shigeru Hirayama(et al)
  3. 日産技報 no.27 レ-ザレ-ダの追突警報裝置への應用 Itsuro Mutamoto(et al)
  4. 自動車技術會論文集(日) v.23 no.3 レ-ザレ-ダを用いた大型トラツクの?追突警報裝置の開發 Yukio Ogawa(et al)
  5. Neural Network Perception for Mobile Robot Guidance Dean A. omerleau
  6. Proceeding of the Second World Congress on Intelligent Transport Systems '95 YOKOHAMA Rear-End-Collision Prevention System Using Image Processing S. Hiroshi;N. Tarsuo;A. Sakae
  7. Journal of Commercial Vechicle, SAE 942284 v.103 VECTOR-A Vision Enhanced/Controlled Truck for Operational Research T. Zimmermann;A. Fuchs;U. Franke;B. Klingenberg
  8. 무인자동차 개발연구, 고려대학교 崔鎭旭
  9. Comm. ACM v.15 no.1 Use of the Hough Transformation to Detect Lines and Curves in Pictures R. O. Duda;P. E. Hart
  10. Massachusetts Institute of Technology An Introduction to neural network J. A. Anderson
  11. Digital Image Processing R.C. Gonzalez;R.E. Woods
  12. Digital Image Processing Algorithms I. Pitas
  13. Machine Vision E.R. Davies
  14. 화상거리를 이용한 도로의 차선인식 이준웅;장인수;강동중;권인소