CALL FOR PAPERS :
DEC-2018
| Submission Last Date |
:
|
30-Dec-2018
|
| Acceptance Notification
|
:
|
in 15 days
|
| Publication Date
|
:
|
in 5 days
|
FOR AUTHORS
FOR REVIEWERS
IJRET® PUBLICATIONS
DOWNLOADS
CONTACT US
NEWS & UPDATES
|
A NEW MULTIMODEL APPROACH FOR HUMAN AUTHENTICATION: SCLERA VEIN AND FINGER VEIN RECOGNITION
G.Radha, C.Saranya, B.Suganyadevi
Abstract: The vein structure is stable over time and can be manipulated for identifying human. The sclera portion of the human eye has blood vessel pattern which is unique for each human being. So, the sclera vein pattern can be used for a useful biometric feature. A few research works has been done over finger vein pattern recognition. Finger vein is an important biometric technique for personal identification and authentication. The finger vein is a blood vessel network under the finger skin. The network pattern is distinct for each individual, unaffected by aging and it is internal i.e. inside human skin which can always guarantee more security authentication. Sclera vein pattern recognition can face a few challenges like: the vein structure moves as the eye moves, low image quality, multilayered structure of the sclera vein and thickness of the sclera vein changes with the excitement level of the human body. To overcome this limitation, the multimodel biometrics is proposed through which the user can be authenticated either sclera vein or finger vein recognition. Sclera vein recognition used Y-shape descriptor and finger vein recognition used repeated line tracking based feature extraction method to effectively eliminate the most unlikely matches respectively. According to the available work in literatures and commercial utilization experiences, sclera vein and finger vein multimodality ensures higher performance and spoofing resistance. Thus building the multimodel biometric system increases the population coverage and improves the accuracy of the human recognition
Keywords: Sclera Vein Recognition, Sclera Feature Matching, Sclera Matching, Sclera Segmentation, Feature Extraction, Finger Vein Recognition, Multimodel Biometrics.
DOI: https://doi.org/10.15623/ijret.2015.0403015
|
|