2011³â Ãß°èÇмú´ëȸ
Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
ÅͳΠ¿µ»ó À¯°í °¨Áö ½Ã½ºÅÛ¿¡¼ Á¤Â÷ °ËÃâ ¾Ë°í¸®Áò |
¿µ¹®Á¦¸ñ(English Title) |
The Stopped Vehicle Detection in the Tunnel Incident Surveillance System |
ÀúÀÚ(Author) |
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À̱ÙÈÄ
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À¯À±½Ä
Gyu-Yeung Kim
Geun-Hoo Lee
Hyun-Tae Kim
Jae-Ho Kim
Yun-Sik Yu
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¿ø¹®¼ö·Ïó(Citation) |
VOL 15 NO. 02 PP. 0607 ~ 0608 (2011. 10) |
Çѱ۳»¿ë (Korean Abstract) |
º» ³í¹®¿¡¼´Â ÅͳΠ³»¿¡ Á¤ÁöÇÑ Â÷·®¿¡ ´ëÇÑ °ËÃâ ¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. Á¦¾È ¾Ë°í¸®ÁòÀº ¹è°æ ÃßÁ¤À» ÅëÇÏ¿© °´Ã¼¸¦ ºÐ¸®ÇÏ°í, Â÷·®µî Ä÷¯ Á¤º¸ÀÇ ½ÇÇèÀû ºÐ¼®À» ÅëÇÏ¿© È¿°úÀûÀ¸·Î Â÷·®À» °ËÃâ ÇÏ¿´´Ù. ¸ðÀÇ ½ÇÇè °á°ú´Â ÅͳΠ¿µ»ó¿¡ ´ëÇÏ¿© 95% ÀÌ»óÀÇ Á¤Áö Â÷·® °ËÃâÀ²À» º¸¿©ÁØ´Ù.
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¿µ¹®³»¿ë (English Abstract) |
In this paper, we propose stopped vehicle detection algorithm in the tunnel. It is shown that our method distinguished objects from background estimated image, and then detected stopped vehicles efficiently based on the experimental analysis about the color information of their lamps. The simulation results show the detection rate is achieved over 95% in the tunnel image.
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Å°¿öµå(Keyword) |
Rear Lamp
Background Estimation
Stopped Vehicle
Detection
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ÆÄÀÏ÷ºÎ |
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