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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö B

Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö B

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) 2D ÅÙ¼­ º¸Æÿ¡ ±â¹Ý ÇÑ ¼Õ»óµÈ ÅؽºÆ® ¿µ»óÀÇ º¹¿ø ¹× ºÐÇÒ
¿µ¹®Á¦¸ñ(English Title) Corrupted Region Restoration based on 2D Tensor Voting and Segmentation
ÀúÀÚ(Author) ¹ÚÁ¾Çö   Nguyen Dinh Toan   ÀÌ±Í»ó   Jonghyun Park   Nguyen Dinh Toan   Lee Gueesang  
¿ø¹®¼ö·Ïó(Citation) VOL 15-B NO. 03 PP. 0205 ~ 0210 (2008. 06)
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(Korean Abstract)
º» ³í¹®¿¡¼­´Â ÀâÀ½¿¡ ÀÇÇØ ¼Õ»óµÈ ÅؽºÆ® ¿µ»óÀ¸·ÎºÎÅÍ º¹¿ø ¹× ºÐÇÒÀ» À§ÇÑ »õ·Î¿î Á¢±Ù ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. Á¦¾ÈµÈ ¹æ¹ýÀº ¼Õ»óµÈ ¿µ¿ªÀÇ º¹¿øÀ» À§ÇÏ¿© »ö»ó ¹× ºñ»ö»ó ¼ººÐÀ» 2Â÷ ´ëĪ ½ºÆ½ ÅÙ¼­·Î Ç¥ÇöÇÏ°í º¸Æà ±â¹ÝÀÇ ¼Õ»óµÈ ¿µ¿ªÀ» º¹¿øÇÏ¿´À¸¸ç, ¸¶Áö¸·À¸·Î Ŭ·¯½ºÅ͸µ ¹æ¹ý¿¡ ÀÇÇØ ºÐÇÒÀ» ¼öÇàÇÑ´Ù. ¸ÕÀú ¿ì¸®´Â Á¦¾ÈµÈ »ö»ó ¼±ÅÃÇÔ¼ö¿¡ ÀÇÇØ ÀâÀ½¿¡ °­°ÇÇÑ »ö»ó°ú ºñ»ö»ó ¼ººÐÀ» ¼±ÅÃÇÑ´Ù. µÎ ¹ø° ´Ü°è¿¡¼­´Â °¢°¢ÀÇ ¼±ÅÃµÈ Æ¯Â¡ º¤Å͵éÀº ½ºÆ½ ÅÙ¼­·Î Ç¥ÇöÇÏ¿´À¸¸ç Á¦ÇÑµÈ º¸Æà Ŀ³ÎÀÇ Çʵ峻¿¡¼­ ÀÌ¿ôÇÏ´Â º¸Å͵é°ú Åë½ÅÀ» ÅëÇÏ¿© »õ·Ó°Ô Á¤ÀǵȴÙ. µû¶ó¼­ 2Â÷ º¸Æà ÈÄ °¢°¢ÀÇ ½ºÆ½ ÅÙ¼­´Â ÀÌ¿ôÇÏ´Â ÅÙ¼­¿Í °°Àº Ư¼ºÀ» °¡Áö¸ç ¼Õ»óµÈ ¿µ¿ªµéÀ» º¹¿øÇÒ ¼ö ÀÖ´Ù. ¸¶Áö¸·À¸·Î º¹¿øµÈ ¿µ»óÀÇ ¼º´ÉÀ» Æò°¡Çϱâ À§ÇÏ¿© ÀûÀÀÀû Æò±Õ À̵¿ ¾Ë°í¸®Áò°ú Ŭ·¯½ºÅ͸µ ¾Ë°í¸®ÁòÀ» ÀÌ¿ëÇÏ¿© ¿µ»ó ºÐÇÒÀ» ¼öÇàÇÏ¿´´Ù. ½ÇÇè¿¡¼­ Á¦¾ÈµÈ ¹æ¹ýÀº ÀüüÀûÀΠ󸮰úÁ¤À» ÀÚµ¿ÀûÀ¸·Î ¼öÇà °¡´ÉÇÏ¿´À¸¸ç ¹è°æ ¹× °´Ã¼ÀÇ ¿µ¿ª¿¡¼­ È¿À²ÀûÀÎ º¹¿ø ¹× ºÐÇÒÀ» ¼öÇàÇÒ ¼ö ÀÖ¾ú´Ù.
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(English Abstract)
A new approach is proposed for restoration of corrupted regions and segmentation in natural text images. The challenge is to fill in the corrupted regions on the basis of color feature analysis by second order symmetric stick tensor. It is show how feature analysis can benefit from analyzing features using tensor voting with chromatic and achromatic components. The proposed method is applied to text images corrupted by manifold types of various noises. Firstly, we decompose an image into chromatic and achromatic components to analyze images. Secondly, selected feature vectors are analyzed by second- order symmetric stick tensor. And tensors are redefined by voting information with neighbor voters, while restore the corrupted regions. Lastly, mode estimation and segmentation are performed by adaptive mean shift and separated clustering method respectively. This approach is automatically done, thereby allowing to easily fill-in corrupted regions containing completely different structures and surrounding backgrounds. Applications of proposed method include the restoration of damaged text images; removal of superimposed noises or streaks. We so can see that proposed approach is efficient and robust in terms of restoring and segmenting text images corrupted.
Å°¿öµå(Keyword) ½ºÆ½ ÅÙ¼­   º¸Æà  º¹¿ø   ÅؽºÆ® ¿µ»ó ºÐÇÒ   Stick Tensor   Voting   Restoration   Text Image Segmentation  
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