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Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2014³â Ãß°èÇмú´ëȸ

2014³â Ãß°èÇмú´ëȸ

Current Result Document : 9 / 20 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) Â÷·®¿ë ºí·¢¹Ú½º ¿µ»ó¿¡¼­ÀÇ ½Ç½Ã°£ ±â»óÁ¤º¸ °ËÁö
¿µ¹®Á¦¸ñ(English Title) Detection of The Real-time Weather Information from a Vehicle Black Box
ÀúÀÚ(Author) °­Áֹ̠  ÀÌÀ缺   Ju-mi Kang   Jaesung Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 18 NO. 02 PP. 0320 ~ 0323 (2014. 10)
Çѱ۳»¿ë
(Korean Abstract)
¿À´Ã³¯ ±³Åëȯ°æÀÇ °íµµÈ­´Â Áö´ÉÇü ±³Åë ½Ã½ºÅÛ(Intelligent Transportation System)°ú ÇÔ²² ÁøÇàµÇ°í ÀÖÀ¸¸ç Â÷·®¿ë ºí·¢¹Ú½º, ¸ð¹ÙÀϱâ±â µîÀÇ ´ëÁßÈ­¿Í ÇÔ²² ¾ÈÀüÇÏ°í Æí¸®ÇÑ ¼­ºñ½º¸¦ Á¦°øÇϴµ¥ ÀÏÁ¶ÇÏ°í ÀÖ´Ù. ±³Åë»óȲÀº ´Ù¾çÇÑ ¿øÀο¡ ÀÇÇØ ½Ã½Ã°¢°¢ º¯È­Çϸç, ƯÈ÷ °©ÀÛ½º·¯¿î Æø¿ì, ¿ì¹Ú, ´«±æ µî°ú °°ÀÌ °ø°øÀÇ ÈûÀ¸·Î Á¦¾îÇÒ ¼ö ¾ø´Â ¿ÜºÎ ¿äÀÎÀ¸·Î ÀÎÇØ ¿îÀüÀÚ°¡ À̸¦ ´ëºñÇÏÁö ¸øÇÏ¿© Å« »ç°í·Î À̾îÁö´Â °æ¿ì°¡ ºñÀϺñÀçÇÏ´Ù. À̸¦ ¹æÁöÇϱâ À§ÇØ ¿îÀüÀÚ°£ ½Ç½Ã°£À¸·Î ±â»óÁ¤º¸¸¦ Àü´ÞÇÏ´Â ½Ã½ºÅÛÀÌ ÇÊ¿äÇÏ´Ù. º» ³í¹®Àº ½Ç½Ã°£ ±â»óÁ¤º¸Àü´ÞÀ» À§ÇÑ ±â»óÁ¤º¸ °ËÁö¾Ë°í¸®ÁòÀ» Á¦¾ÈÇÑ´Ù. º» ¾Ë°í¸®ÁòÀº ¿ÍÀÌÆÛÀÇ ¿òÁ÷ÀÓ°ú ¸¼Àº³¯ÀÇ È÷½ºÅä±×·¥ °£ Contrast¸¦ ÀÌ¿ëÇÏ¿© ±â»ó»óȲÀ» °ËÁöÇÑ´Ù. ÀϹÝÀûÀ¸·Î ¾ÇõÈÄ »óȲ¿¡¼­ ¿ÍÀÌÆÛ¸¦ »ç¿ëÇÏ°Ô µÇ¸ç, ´«À̳ª ºñ µî¿¡ µû¶ó ´Ù¸¥ Contrast°ªÀ» °¡Áö°Ô µÈ´Ù. À̸¦ ÀÌ¿ëÇØ ¸¼Àº »óȲ, ´«ÀÌ ¿À´Â »óȲ, ´«ÀÌ ½×ÀÎ »óȲ, ºñ¿À´Â »óȲ µîÀ» ÆÇ´ÜÇÏ¿´´Ù. ¿ì¼±, ¿¬»ê·®À» ÁÙÀ̱â À§ÇØ ¿ÍÀÌÆÛ¸¦ °ËÁöÇÒ ¼ö ÀÖ´Â ÃÖ¼Ò¿µ¿ªÀ» ROI(Region Of Interest)·Î ÁöÁ¤ÇÏ°í, Â÷·® ¿ÍÀÌÆÛÀÇ ¹à±â¸¦ ÀÓ°è°ªÀ¸·Î ÇÏ´Â Thresholding ¿¬»êÀ» ÅëÇØ ¿ÍÀÌÆÛ¸¦ °ËÃâÇÏ¿´´Ù. ¶ÇÇÑ, ¸¼Àº ³¯°ú ¾ÇõÈÄ»óȲÀÇ Value °ªÀ» ÀÌ¿ëÇØ Contrast¸¦ ±¸ÇÏ¿´À¸¸ç À̸¦ ÅëÇØ °¢°¢ÀÇ ±â»ó»óȲÀ» ±¸º°ÇÏ¿´´Ù. ½ÇÇè°á°ú ºñ¿À´Â »óȲÀº ¾à 87%, ´«ÀÌ ³»¸®´Â »óȲÀº ¾à 82% °ËÁöÀ²À» ¾òÀ» ¼ö ÀÖ¾ú´Ù.
¿µ¹®³»¿ë
(English Abstract)
Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.
Å°¿öµå(Keyword) Image processing   Weather Detection   Contrast   Region of Interest  
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