Paper Info
Title
An optimized multimodal biometric system with hierachical classifiers and reduced features
Abstract
The paper presents an optimized multimodal biometric system for identification applications. This solution is based on innovative and computational-efficient biometric data hierarchical classifiers (with detection and discrimination stages) and also with a post-classification fusion. The detection-based classification is very suitable for applications with several security levels in which the end-users have various authorization degrees. The proposed solution supports an optimal trade-off between the identification accuracy and the computational complexity, which is important for the medium- and large-scale identification biometric applications.
Year
DOI
Venue
2014
10.1109/MeMeA.2014.6860060
MeMeA
Keywords
Field
DocType
detection-based classification,hierarchical classifier,image fusion,biometric data hierarchical classifiers,identification,post-classification fusion,computational complexity,biometrics (access control),image classification,reduced features,rejection threshold,medium-scale identification biometric application,optimized multimodal biometric system,optimal trade-off,large-scale identification biometric application,detectors,iris recognition,fingerprint recognition,security,accuracy
Signature recognition,Pattern recognition,Computer science,Authorization,Speech recognition,Artificial intelligence,Biometric data,Biometrics,Biometric system,Computational complexity theory
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Sorin Soviany101.35
Sorin Puscoci200.34