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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) Â÷ ¿¬»ê°ú ART2 ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÑ Â÷·® ¹øÈ£ÆÇ ÅëÇÕ ÀνÄ
¿µ¹®Á¦¸ñ(English Title) Recognition of Car License Plates Using Difference Operator and ART2 Algorithm
ÀúÀÚ(Author) ±è±¤¹é   ±è¼ºÈÆ   ¿ì¿µ¿î   Kwang-Baek Kim   Seong Hoon Kim   Young Woon Woo  
¿ø¹®¼ö·Ïó(Citation) VOL 13 NO. 11 PP. 2277 ~ 2282 (2009. 11)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â ÇüÅÂÇÐÀû Ư¡ ¹× Â÷ ¿¬»ê°ú ART2 ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÑ Â÷·® ¹øÈ£ÆÇ ÀÎ½Ä ¹æ¹ýÀ» Á¦¾ÈÇÏ¿´´Ù. ¹«ÀÎ Ä«¸Þ¶ó¿¡¼­ ȹµæµÈ Â÷·® ¹øÈ£ÆÇ ¿µ»ó¿¡¼­ Â÷ ¿¬»êÀ» ÀÌ¿ëÇÏ¿© ¿¡Áö¸¦ ÃßÃâÇÑ ÈÄ¿¡ ºí·Ï ÀÌÁøÈ­ÇÑ´Ù. ÀÌÁøÈ­µÈ Â÷·® ¿µ»ó¿¡¼­ ½Å¡¤±¸ Â÷·® ¹øÈ£ÆÇÀÇ ÇüÅÂÇÐÀû Ư¼ºÀ» 8¹æÇâ À±°û¼± ÃßÀû ¾Ë°í¸®Áò¿¡ Àû¿ëÇÏ¿© ÀâÀ½ ¿µ¿ªÀ» Á¦°ÅÇÏ°í, Â÷·®ÀÇ ¹øÈ£ÆÇ ¿µ¿ªÀ» ÃßÃâÇÑ´Ù. ÃßÃâµÈ ¹øÈ£ÆÇ ¿µ¿ª¿¡ ´ëÇÏ¿© Æò±Õ ÀÌÁøÈ­¿Í ÃÖ´ë․ÃÖ¼Ò ÀÌÁøÈ­¸¦ Àû¿ëÇÏ¿© ¹øÈ£ÆÇÀÇ °³º° ¿µ¿ª¿¡ ´ëÇÑ ÇüÅÂÇÐÀû Ư¼ºÀ» °í·ÁÇÏ¿© ÀâÀ½À» Á¦°ÅÇÏ°í, Labeling ¾Ë°í¸®ÁòÀ» Àû¿ëÇÏ¿© °³º° ¹®ÀÚ¸¦ ÃßÃâÇÑ ÈÄ¿¡ °áÇÕÇÑ´Ù. ÀÌ·¸°Ô ÃßÃâµÇ¾î °áÇÕµÈ °³º° ¹®ÀÚ ¹× ¼ýÀÚ ÄÚµåµéÀº ART2 ¾Ë°í¸®Áò¿¡ Àû¿ëÇÏ¿© ÇнÀ ¹× ÀνĵȴÙ. Á¦¾ÈµÈ Â÷·® ¹øÈ£ÆÇ ÃßÃâ ¹× ÀÎ½Ä ¹æ¹ýÀÇ ¼º´ÉÀ» Æò°¡Çϱâ À§ÇØ ³ì»ö ¹øÈ£ÆÇ°ú Èò»ö ¹øÈ£ÆÇ À̹ÌÁö °¢°¢ 100ÀåÀ» ´ë»óÀ¸·Î ½ÇÇèÇÑ °á°ú, Á¦¾ÈµÈ Â÷·® ¹øÈ£ÆÇ ÃßÃâ ¹× ÀÎ½Ä ±â¹ýÀÌ È¿À²ÀûÀÓÀ» È®ÀÎÇÏ¿´´Ù.
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(English Abstract)
In this paper, we proposed a new recognition method can be used in application systems using morphological features, difference operators and ART2 algorithm. At first, edges are extracted from an acquired car image by a camera using difference operators and the image of extracted edges is binarized by a block binarization method. In order to extract license plate area, noise areas are eliminated by applying morphological features of new and existing types of license plate to the 8-directional edge tracking algorithm in the binarized image. After the extraction of license plate area, mean binarization and mini-max binarization methods are applied to the extracted license plate area in order to eliminated noises by morphological features of individual elements in the license plate area, and then each character is extracted and combined by Labeling algorithm. The extracted and combined characters(letter and number symbols) are recognized after the learning by ART2 algorithm. In order to evaluate the extraction and recognition performances of the proposed method, 200 vehicle license plate images (100 for green type and 100 for white type) are used for experiment, and the experimental results show the proposed method is effective.
Å°¿öµå(Keyword) Â÷ ¿¬»ê   ART2   ºí·Ï ÀÌÁøÈ­   ¹øÈ£ÆÇ ÀνĠ  Difference Operator   ART2   Block Binarization   Recognition of a Car License Plate  
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