ÇѱÛÁ¦¸ñ(Korean Title) |
¼Õ°¡¶ô Á¤·Ä°ú ȸÀü¿¡ °ÀÎÇÑ ºñ Á¢ÃË½Ä ¼Õ°¡¶ô Á¤¸Æ ÀÎ½Ä ¿¬±¸ |
¿µ¹®Á¦¸ñ(English Title) |
A Study on Touchless Finger Vein Recognition Robust to the Alignment and Rotation of Finger |
ÀúÀÚ(Author) |
À念±Õ
°º´ÁØ
¹Ú°·É
Young Kyoon Jang
Byung Jun Kang
Kang Ryoung Park
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¿ø¹®¼ö·Ïó(Citation) |
VOL 15-B NO. 04 PP. 0275 ~ 0284 (2008. 08) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù °³ÀÎÀÇ Á¤º¸ º¸È£¿¡ ´ëÇÑ Á߿伺ÀÌ Áõ°¡ÇÔ¿¡ µû¶ó »ýü ÀÎ½Ä ±â¼úÀÌ ÃâÀÔ ÅëÁ¦ ½Ã½ºÅÛ ¶Ç´Â °³ÀÎ ÀÎÁõ, ÀÎÅÍ³Ý ¹ðÅ·, ATM ±â±â µî ¿©·¯ ÀÀ¿ë¿¡¼ »ç¿ëµÇ¾îÁö°í ÀÖ´Ù. ¼Õ°¡¶ô Á¤¸Æ ÀνÄÀ̶õ »ç¶÷¸¶´Ù °íÀ¯ÇÑ ¼Õ°¡¶ô Á¤¸Æ ÆÐÅÏ Á¤º¸¸¦ »ç¿ëÇÏ´Â °í ½Å·ÚµµÀÇ »ýü ÀÎ½Ä ±â¼úÀÌ´Ù. º» ¿¬±¸¿¡¼´Â ºñ Á¢ÃË½Ä ¼Õ°¡¶ô Á¤¸Æ ÀνÄÀ» À§ÇÑ »õ·Î¿î ÀåÄ¡ ¹× ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. º» ¿¬±¸´Â ±âÁ¸ÀÇ ¿¬±¸¿¡ ºñÇØ ´ÙÀ½°ú °°Àº ´Ù¼¸ °¡ÁöÀÇ ÀåÁ¡À» ³ªÅ¸³»°í ÀÖ´Ù. ù°, º» ³í¹®¿¡¼ Á¦¾ÈÇÏ´Â Àåºñ´Â »ç¿ëÀÚÀÇ ¼Õ°¡¶ô Á¤¸Æ ¿µ»ó Ãëµæ ½Ã, ¼Õ°¡¶ôÀÇ µÞ¸é°ú ¼Õ°¡¶ô ³¡, ¿·À» ÁöÁöÇÒ ¼ö ÀÖ´Â ÃÖ¼ÒÇÑÀÇ ÁöÁö´ë¸¸À» »ç¿ëÇÔÀ¸·Î½á »ç¿ëÀÚÀÇ ºÒÄè°¨À» ÃÖ¼ÒÈÇÒ ¼ö ÀÖ´Ù. µÑ°, ¼Õ°¡¶ô Á¤¸Æ ¿µ»óÀ» ÃëµæÇϱâ À§ÇÑ Ä«¸Þ¶ó ¾Õ¿¡ 45µµ ±â¿ï¾îÁø ÇÖ ¹Ì·¯(hot mirror)¸¦ »ç¿ëÇÔÀ¸·Î½á, ¼Õ°¡¶ô Á¤¸Æ ¿µ»ó Ãëµæ ÀåÄ¡ÀÇ µÎ²²¸¦ ÁÙÀÏ ¼ö ÀÖ¾ú´Ù. ÀÌ´Â ÇÚµåÆù°ú °°ÀÌ µÎ²²¿¡ Á¦ÇÑÀÌ ÀÖ´Â ¿©·¯ ÀÀ¿ë ºÐ¾ß¿¡¼ ³Î¸® »ç¿ëµÉ ¼ö ÀÖÀ½À» ÀǹÌÇÑ´Ù. ¼Â°, º» ¿¬±¸¿¡¼´Â LBP(Local Binary Pattern) ¹æ¹ýÀ» ±â¹ÝÀ¸·Î ¼Õ°¡¶ô Á¤¸ÆÀÇ Æ¯Â¡ Á¤º¸¸¦ ÃßÃâÇÔÀ¸·Î½á ºÎºÐÀûÀ¸·Î ½ÉÇÏ°Ô ¾îµÓ°Å³ª ¹àÀº ¿µ¿ªÀ» Æ÷ÇÔÇÏ´Â ±ÕÀÏÇÏÁö ¾ÊÀº Á¶¸íÀÇ ¿µÇâÀ» ÁÙÀÏ ¼ö ÀÖ¾ú´Ù. ³Ý°, ºñ Á¤¸Æ ¿µ¿ªÀ» ÀνĿ¡ »ç¿ëÇÏÁö ¾ÊÀ½À¸·Î½á ÀÎ½Ä ¼º´ÉÀ» º¸´Ù Çâ»ó ÇÒ ¼ö ÀÖ¾ú´Ù. ´Ù¼¸Â°, ÃßÃâµÈ ¼Õ°¡¶ô Á¤¸Æ Äڵ带 ±â µî·ÏµÈ ÄÚµå¿Í ¸ÅĪ ½Ã, ¼öÆò ¹× ¼öÁ÷¹æÇâ ºñÆ® À̵¿ ¹æ¹ýÀ» »ç¿ëÇÔÀ¸·Î½á ¿µ»ó Ãëµæ ½Ã ¼Õ°¡¶ôÀÇ ¿òÁ÷ÀÓ°ú ȸÀü¿¡ ÀÇÇÑ º»Àε¥ÀÌÅÍÀÇ º¯Èµµ¸¦ ÁÙÀÏ ¼ö ÀÖ¾ú´Ù. ½ÇÇè °á°ú, º» ³í¹®¿¡¼ Á¦¾ÈÇÏ´Â ¼Õ°¡¶ô Á¤¸Æ ÀνĹæ¹ýÀÇ EER(Equal Error Rate)Àº 0.07423%¿´°í Àüü ó¸® ½Ã°£Àº 91.4ms¿´´Ù. |
¿µ¹®³»¿ë (English Abstract) |
With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms. |
Å°¿öµå(Keyword) |
»ýü ÀνÄ
ºñÁ¢ÃË½Ä ¼Õ°¡¶ô Á¤¸Æ ÀνÄ
Biometrics
touchless finger vein recognition
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