• 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¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) Á¶¸í º¯È­ ȯ°æ¿¡¼­ ¾ó±¼ ÀνÄÀ» À§ÇÑ Non-Alpha Weberface ¹× È÷½ºÅä±×·¥ ÆòÈ°È­ ±â¹Ý ¾ó±¼ Ç¥Çö
¿µ¹®Á¦¸ñ(English Title) Face Representation Based on Non-Alpha Weberface and Histogram Equalization for Face Recognition Under Varying Illumination Conditions
ÀúÀÚ(Author) ±èÇÏ¿µ   ÀÌÈñÀç   À̻󱹠  Ha-Young Kim   Hee-Jae Lee   Sang-Goog Lee  
¿ø¹®¼ö·Ïó(Citation) VOL 44 NO. 03 PP. 0295 ~ 0305 (2017. 03)
Çѱ۳»¿ë
(Korean Abstract)
¾ó±¼ ¿ÜÇüÀº Á¶¸íÀÇ ¿µÇâÀ» Å©°Ô ¹Þ±â ¶§¹®¿¡ Á¶¸í º¯È­´Â ¾ó±¼ ÀÎ½Ä ½Ã½ºÅÛÀÇ ¼º´ÉÀ» ÀúÇϽÃÅ°´Â ¿äÀÎ Áß ÇϳªÀÌ´Ù. º» ³í¹®¿¡¼­´Â non-alpha Weberface(non-alpha WF)¿Í È÷½ºÅä±×·¥ ÆòÈ°È­¸¦ °áÇÕÇÏ¿© Á¶¸í º¯È­¿¡ °­°ÇÇÑ ¾ó±¼ Ç¥Çö ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. ¸ÕÀú, ÀÔ·Â ¾ó±¼ ¿µ»ó¿¡ ´ëÇØ ¸í¾Ï ´ëºñ Á¶Àý ÆĶó¹ÌÅ͸¦ Àû¿ëÇÏÁö ¾ÊÀº non-alpha WF¸¦ »ý¼ºÇÑ´Ù. ÀÌÈÄ, non-alpha WFÀÇ È÷½ºÅä±×·¥ ºÐÆ÷¸¦ Àü¿ªÀûÀ¸·Î ±ÕÀÏÇÏ°Ô ÇÏ°í ¸í¾Ï ´ëºñ¸¦ Çâ»ó½ÃÅ°±â À§ÇØ È÷½ºÅä±×·¥ ÆòÈ°È­¸¦ ¼öÇàÇÑ´Ù. Á¦¾ÈÇÏ´Â ¹æ¹ýÀ» ÅëÇØ Àüó¸®µÈ ¾ó±¼ ¿µ»óÀ¸·ÎºÎÅÍ ÀúÂ÷¿ø ÆǺ° Ư¡À» ÃßÃâÇϱâ À§ÇØ (2D)©÷PCA¸¦ Àû¿ëÇÑ´Ù. Extended Yale B ¹× CMU PIE ¾ó±¼ µ¥ÀÌÅͺ£À̽º¿¡ ´ëÇØ ½ÇÇèÇÑ °á°ú, Á¦¾ÈÇÏ´Â ¹æ¹ýÀ¸·Î °¢°¢ 93.31%¿Í 97.25%ÀÇ Æò±Õ ÀνķüÀ» ¾ò¾ú´Ù. ¶ÇÇÑ, Á¦¾ÈÇÏ´Â ¹æ¹ýÀº ±âÁ¸ WF»Ó¸¸ ¾Æ´Ï¶ó ¿©·¯ Á¶¸í ó¸® ¹æ¹ýµé°ú ºñ±³ÇÏ¿© Çâ»óµÈ ÀÎ½Ä ¼º´ÉÀ» º¸¿´´Ù.
¿µ¹®³»¿ë
(English Abstract)
Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. (2D)©÷PCA is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.
Å°¿öµå(Keyword) ¾ó±¼ ÀνĠ  Á¶¸í º¯È­   ¾ó±¼ Ç¥Çö   Weberface   È÷½ºÅä±×·¥ ÆòÈ°È­   (2D)©÷PCA   face recognition   illumination variation   face representation   Weberface   histogram equalization   (2D)©÷PCA  
ÆÄÀÏ÷ºÎ PDF ´Ù¿î·Îµå