Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng
Finger vein identification has become an important area of study especially in the field of biometric identification and has further potential in the field of forensics. The finger vein pattern has highly discriminative features that exhibit universality, uniqueness and permanence characteristics...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Teknologi MARA, Kedah
2019
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| Online Access: | https://ir.uitm.edu.my/id/eprint/30605/ |
| _version_ | 1848807540972847104 |
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| author | Hani Yahaya, Yuhanim Shamsuddin, Siti Mariyam Won, Yee Leng |
| author_facet | Hani Yahaya, Yuhanim Shamsuddin, Siti Mariyam Won, Yee Leng |
| author_sort | Hani Yahaya, Yuhanim |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | Finger vein identification has become an important area of study especially in the field of
biometric identification and has further potential in the field of forensics. The finger vein pattern
has highly discriminative features that exhibit universality, uniqueness and permanence
characteristics. Finger vein identification requires living body identification, which means that
only vein in living finger can be captured and used for identification. Acquiring useful features
from finger vein in order to reflect the identity of an individual is the main issues for
identification. This research aims at improving the scheme of finger vein identification take
advantage of the proposed feature extraction, which is Maximum Curvature Directional Feature
(MCDF). Experimental results based on two public databases, SDUMLA-HMT datasets and
PKU datasets show high performance of the proposed scheme in comparison with state-of-the
art methods. The proposed approach scored 0.001637 of equal error rate (EER) for SDUMLAHMT dataset and 0.00431 of equal error rate for PKU dataset |
| first_indexed | 2025-11-14T22:44:27Z |
| format | Article |
| id | uitm-30605 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:44:27Z |
| publishDate | 2019 |
| publisher | Universiti Teknologi MARA, Kedah |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-306052021-01-14T17:42:57Z https://ir.uitm.edu.my/id/eprint/30605/ Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng cpit Hani Yahaya, Yuhanim Shamsuddin, Siti Mariyam Won, Yee Leng Information technology. Information systems Pattern recognition systems Finger vein identification has become an important area of study especially in the field of biometric identification and has further potential in the field of forensics. The finger vein pattern has highly discriminative features that exhibit universality, uniqueness and permanence characteristics. Finger vein identification requires living body identification, which means that only vein in living finger can be captured and used for identification. Acquiring useful features from finger vein in order to reflect the identity of an individual is the main issues for identification. This research aims at improving the scheme of finger vein identification take advantage of the proposed feature extraction, which is Maximum Curvature Directional Feature (MCDF). Experimental results based on two public databases, SDUMLA-HMT datasets and PKU datasets show high performance of the proposed scheme in comparison with state-of-the art methods. The proposed approach scored 0.001637 of equal error rate (EER) for SDUMLAHMT dataset and 0.00431 of equal error rate for PKU dataset Universiti Teknologi MARA, Kedah 2019 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/30605/1/AJ_YUHANIM%20HANI%20YAHAYA%20CPLT%20K%2019.pdf Hani Yahaya, Yuhanim and Shamsuddin, Siti Mariyam and Won, Yee Leng (2019) Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng. (2019) Journal of Creative Practices in Language Learning and Teaching (CPLT) <https://ir.uitm.edu.my/view/publication/Journal_of_Creative_Practices_in_Language_Learning_and_Teaching_=28CPLT=29.html>, 7 (1). pp. 42-48. ISSN 1823-464X https://cplt.uitm.edu.my/ |
| spellingShingle | Information technology. Information systems Pattern recognition systems Hani Yahaya, Yuhanim Shamsuddin, Siti Mariyam Won, Yee Leng Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title | Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title_full | Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title_fullStr | Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title_full_unstemmed | Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title_short | Finger vein identification based on maximum curvature directional feature extraction / Yuhanim Hani Yahaya, Siti Mariyam Shamsuddin and Wong Yee Leng |
| title_sort | finger vein identification based on maximum curvature directional feature extraction / yuhanim hani yahaya, siti mariyam shamsuddin and wong yee leng |
| topic | Information technology. Information systems Pattern recognition systems |
| url | https://ir.uitm.edu.my/id/eprint/30605/ https://ir.uitm.edu.my/id/eprint/30605/ |