Robust Authentication Using Fast and Self Consistent Estimation for the Match Score Fusion

2019 ◽  
Author(s):  
Long Tran ◽  
Le Hoang Thai
Keyword(s):  
Consistent Estimation ◽  
Self Consistent ◽  
Score Fusion ◽  
Match Score

MATCH SCORE FUSION OF FINGERPRINT AND FACE BIOMETRICS FOR VERIFICATION

2015 ◽  
Vol 77 (18) ◽  
Author(s):  
Chiung Ching Ho ◽  
Mufaddal Ali Hussin ◽  
Hu Ng
Keyword(s):  
Feature Vector ◽  
Product Rule ◽  
New Approach ◽  
Biometric Systems ◽  
Score Fusion ◽  
Face Biometrics ◽  
Match Score

In recent years, attacks on password databases have been carried out at an increasing rate, with significant success. Thus, a new approach is needed to prove one's claim to identity instead of relying on a password. In this paper, we investigate the use of biometric match scores for the purpose of verification. Our work was performed using the BSSR1 multimodal match score biometric dataset, which contains match scores from face and fingerprint biometric systems. We investigated the use of match scores as a feature vector, and performed Simple Sum and Product Rule fusion of match scores. The results we obtained demonstrated that the use of match scores for verification purposes can be achieved to give a result that is highly accurate.

scholarly journals BIOMETRIC SCORE FUSION

2016 ◽  
Vol 2 (6) ◽  
Author(s):  
PANKAJ ,
Keyword(s):  
Frontal Area ◽  
Coarse Grained ◽  
Security Level ◽  
Focal Points ◽  
Biometric Data ◽  
Score Fusion ◽  
Relative Change ◽  
Modular Framework ◽  
Score Combination ◽  
Match Score

Multimodal biometric innovation in light of unique mark and finger knuckle has pulled in footing among scientists as of late. Despite the fact that Uni-modular framework offers many focal points, it has certain intrinsic shortcomings which deny it of the appeal. Uni-modular unique finger impression biometric frameworks performed singular acknowledgment in light of a particular wellspring of biometric data. However the match score esteem must be enhanced by working with low quality little closer view zone biometric pictures. In fact, the confirmation forms delivered by Finger Knuckle Print (FKP) brings about higher relative changes. The distortions between FKP pictures of same finger are of higher extent. The unimodal biometric check framework frequently gets influenced after accomplishing higher match score esteem. Besides, bimodal check framework does not accomplish higher security level which prompts to lesser combination score esteem. To diminish relative change on multimodal biometric framework, NonFracture based Fingerprint and Finger-Knuckle print Biometric Score Fusion (NFF-BSF) component is proposed in this paper. At first, particular estimation of match score is measured utilizing multimodal fitting coarse grained dissemination work. Multimodal fitting coarse grained dissemination capacity is utilized to work with low quality petite frontal area biometric pictures that accomplish high fitting score on the test and preparing biometric pictures. Also, Non-Fracture misshapening handling is completed in NFF-BSF instrument to diminish the adjustment fit as a fiddle of protest by utilizing bend length on biometric picture surfaces. At last, a coordinating technique in NFF-BSF instrument is utilized to decrease the relative changes. Thus, the relative changes on multimodal biometric framework expands the match score combination esteem. Investigation is directed on variables, for example, certifiable acknowledgment rate, coordinating score combination level and blunder rate on multimodal coordinating

Pseudo Self-Consistent Estimation of a Copula Model with Informative Censoring

2005 ◽  
Vol 32 (1) ◽  
pp. 1-20 ◽  
Author(s):  
HONGYU JIANG ◽  
JASON P. FINE ◽  
MICHAEL R. KOSOROK ◽  
RICK CHAPPELL
Keyword(s):  
Informative Censoring ◽  
Copula Model ◽  
Consistent Estimation ◽  
Self Consistent
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