• Àüü
  • ÀüÀÚ/Àü±â
  • Åë½Å
  • ÄÄÇ»ÅÍ
´Ý±â

»çÀÌÆ®¸Ê

Loading..

Please wait....

±¹³» ³í¹®Áö

Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Çѱ¹Á¤º¸Åë½ÅÇÐȸ ³í¹®Áö (Journal of the Korea Institute of Information and Communication Engineering)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ºÎºÐ top-view ¿µ»óÀ» ÀÌ¿ëÇÑ Â÷¼± ÀÌÅ» °ËÃâ
¿µ¹®Á¦¸ñ(English Title) Lane Departure Detection Using a Partial Top-view Image
ÀúÀÚ(Author) ¹ÚÇѵ¿   ¿ÀÁ¤¼ö   Han-dong Park   Jeong-su Oh  
¿ø¹®¼ö·Ïó(Citation) VOL 21 NO. 08 PP. 1553 ~ 1559 (2017. 08)
Çѱ۳»¿ë
(Korean Abstract)
º» ³í¹®Àº ÀÚµ¿Â÷ Àü¹æ¿¡ ÀåÂøµÈ ´ÜÀÏ Ä«¸Þ¶ó¸¦ ÀÌ¿ëÇÑ Â÷¼± ÀÌÅ» °ËÃâ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº Ä«¸Þ¶ó¿¡ ÀÇÇØ ÃëµæµÈ ¿µ»óÀ¸·ÎºÎÅÍ top-view °ø°£¿¡ ÁöÁ¤µÈ ÀÛÀº °ü½É ¿µ¿ªÀ» À§ÇÑ ºÎºÐ top-view ¿µ»óÀ» »ý¼ºÇÏ°í, ÀÛÀº ºÎºÐ top-view ¿µ»ó¿¡¼­ Â÷¼±À» °ËÃâÇÏ°í, ¹Ì¸® ÁöÁ¤µÈ °¡»ó ÀÚµ¿Â÷¿Í °ËÃâµÈ Â÷¼±µéÀÇ °ãħÀ» Á¶»çÇØ Â÷¼± ÀÌÅ»À» °áÁ¤ÇÑ´Ù. ¶ÇÇÑ Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº Â÷¼± »çÀÌ¿¡¼­ Â÷¼± ÀÌÅ» °ËÃâÀ» ¹æÇØÇÏ´Â µµ·Î Ç¥±â (ÀâÀ½)¿¡ ÀÇÇÑ Á÷¼±µéÀÇ Á¦°Å¿Í ÀÌÀü ÇÁ·¹ÀÓÀÇ Â÷¼± Á¤º¸¸¦ ÀÌ¿ëÇÑ ¼Õ½ÇµÈ Â÷¼±ÀÇ ¿¹ÃøÀ» Æ÷ÇÔÇÑ´Ù. ½ÇÁ¦ ÁÖÇà µ¿¿µ»óÀ» ÀÌ¿ëÇÑ Â÷¼± ÀÌÅ» °ËÃâ ½ÇÇè¿¡¼­ Á¦¾ÈµÈ ¾Ë°í¸®ÁòÀº Â÷¼± À¯Áö »óÅ¿¡¼­ 99.0%, Â÷¼± ÀÌÅ» »óÅ¿¡¼­ 94.7%¸¦ Á¤»óÀûÀ¸·Î °ËÃâÇÑ´Ù.
¿µ¹®³»¿ë
(English Abstract)
This paper proposes a lane departure detection algorithm using a single camera equipped in front of a vehicle. The proposed algorithm generates a partial top-view image for a small ROI (region of interest) designated on the top-view space form the image acquired by the camera, detects lanes on the small partial top-view image, and makes a decision on the lane departure by checking overlap between the pre-assigned virtual vehicle and the detected lanes. The proposed algorithm also includes the removal of lines occurred by road symbols (noises) disturbing the lane departure detection between lanes and the prediction of lost lanes using lane information of previous fames. In lane departure detection test using real road videos, the proposed algorithm makes the right decision of 99.0% in lane keeping conditions and 94.7% in lane departure conditions.
Å°¿öµå(Keyword) Â÷¼± ÀÌÅ»   Â÷¼± °ËÃâ   Â÷¼± ¿¹Ãø   ÀÚÀ² ÁÖÇà   top-view ¿µ»ó   Lane Departure   Lane Detection   Lane Prediction   Self Driving   Top-View Image  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå