• 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) CCTV¸¦ ÀÌ¿ëÇÑ ¹Ì¼¼¸ÕÁö ³óµµ À¯Ãß ¹æ¹ý
¿µ¹®Á¦¸ñ(English Title) An Method for Inferring Fine Dust Concentration Using CCTV
ÀúÀÚ(Author) È«¼ø¿ø   ÀÌÀ缺   Sunwon Hong   Jaesung Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 23 NO. 10 PP. 1234 ~ 1239 (2019. 10)
Çѱ۳»¿ë
(Korean Abstract)
º» ³í¹®¿¡¼­´Â Ãß°¡ ¼³ºñ ¾øÀÌ ±âÁ¸ CCTV ¿µ»óÀ» µðÁöÅÐ ¿µ»ó 󸮸¦ ÅëÇÏ¿© ¹Ì¼¼¸ÕÁö ³óµµ¸¦ ÃøÁ¤ÇÏ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. ¿µ»óó¸® ¾Ë°í¸®ÁòÀº ³ëÀÌÁî Á¦°Å, »þÇÁ´×, ROI ÁöÁ¤, ¿§Áö °­µµ °è»ê, HSV º¯È¯À» ÅëÇÑ º¸Á¤ ¼øÀ¸·Î ±¸¼º µÇ¸ç C++ OpenCV ¶óÀ̺귯¸®¸¦ ÀÌ¿ëÇØ ±¸ÇöÇÏ¿´´Ù. ÇÑ´Þµ¿¾È ĸÃÄÇÑ CCTV À̹ÌÁöµé¿¡ º» ¾Ë°í¸®ÁòÀ» Àû¿ëÇÑ °á °ú ROI ¿µ¿ª¿¡ ´ëÇØ °è»êµÈ ¿§Áö °­µµ´Â ¹Ì¼¼¸ÕÁö ³óµµ¿Í ¹ÐÁ¢ÇÑ °ü°è°¡ ÀÖ´Â °ÍÀ¸·Î ³ªÅ¸³µ´Ù. µÎ µ¥ÀÌÅÍ°£ »ó°ü°ü °è¸¦ Ãß·ÐÇÏ°íÀÚ MATLABÀ» ÀÌ¿ëÇÏ¿© °ÅµìÁ¦°ö ¹æÁ¤½Ä ÇüÅÂÀÇ Ãß¼¼¼±À» ¼ö¸³ÇÏ¿´À¸¸ç ±× Ãß¼¼¼±À¸·ÎºÎÅÍ ÀÌÅ»ÇÑ µ¥ÀÌÅÍ Æ÷ÀÎÆ®µéÀÇ °³¼ö´Â 12.5% ³»¿Ü·Î ³ªÅ¸³ª ÀüüÀûÀ¸·Î ¾à 87.5%ÀÇ Á¤È®µµ¸¦ º¸¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
This paper proposes a method for measuring fine dust concentration through digital processing of images captured by only existing CCTVs without additional equipment. This image processing algorithm consists of noise reduction, edge sharpening, ROI setting, edge strength calculation, and correction through HSV conversion. This algorithm is implemented using the C OpenCV library. The algorithm was applied to CCTV images captured over a month. The edge strength values calculated for the ROI region are found to be closely related to the fine dust concentration data. To infer the correlation between the two types fo data, a trend line in the form of a power equation is established using MATLAB. The number of data points deviating from the trend line accounts for around 12.5%. Therefore, the overall accuracy is about 87.5%.
Å°¿öµå(Keyword) Æó¼âȸ·Î ÅÚ·¹ºñÀü   ¿µ»ó ÇÊÅ͸µ   ¹Ì¼¼¸ÕÁö   HSV   Ã߷Р  CCTV   Image filtering   Fine dust   HSV   Inference  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå