A New Biometric Human Identification Based On Fusion Fingerprints and Finger Veins Using monoLBP Descriptor

Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).





References:
[1] H. Kopka and P. W. Daly, Online Palm print Identification,IEEE Trans.
Pattern Analysis and Machine Intelligence,25(2):10411050, 2003.
[2] Jianwei Yang and Lifeng Liu, A modified Gabor filter design
method for fingerprint image enhancement,Pattern Recognition Letters,
24(1):18051817, 2003.
[3] M. Kawagoe and A. Tojo, Fingerprint Pattern Classification,Pattern
Recognition,17(3):295303, 1984.
[4] Arun Vinodh C, Extracting and Enhancing the Core Area in Fingerprint
Images,IJCSNS International Journal of Computer Science and Network
Security,7(11), 2007.
[5] Lin Hong, Yifei Wan and Jain A., Fingerprint image enhancement: algorithm
and performance evaluation,IEEE transactions on pattern analysis
and machine intelligence,20(8):777 789, 1998.
[6] T. Ojala, M. Pietikinen and T. Menp, Online Palm print Identification,
Multiresolution gray-scale and rotation invariant texture classifcation with
local binary patterns,24(1):971 987, 2002.
[7] M. Felsberg and G. Sommer, The monogenic signal, IEEE Trans. SP,
49(1):31363144, 2001.
[8] Timo Ahonen, Abdenour Hadid and Matti Piesetikainen, Face Description
With Local Binary Patterns:Application to Face Recognition,IEEE Transactions
on Pattern Analysis and Machine Intelligence, 28(12):20732041,
2006.
[9] A.Teoch, S. A. Samad and A.hussain, Nearest Neigh- bourhood Classifers
in biometric Fusion,IInternational Journal of the Computer, 12(1):2326,
2004..
[10] S. C. Dass, K. Nandakumar and A. K. Jain, A principal approach
to score level fusion in Multimodal Biometrics System,Proceedings of
ABVPA, 2005.
[11] Hatim A. Aboalsamh, A Multi Biometric System Using Combined Vein
and Fingerprint Identification,International journal of circuits, systems
and signal, processing, 5(1):2936, 2011.