Paper Info
Title
Decision Fusion From Parts And Samples For Robust Iris Recognition
Abstract
Fusion techniques can be used in biometrics to achieve higher accuracy. When biometric systems are in operation and the threat level changes, controlling the trade-off between detection error rates can reduce the impact of an attack. In a fused system, varying a single threshold does not allow this to be achieved, but systematic adjustment of a set of parameters does. In this paper, fused decisions from a multi-part, multi-sample sequential architecture are investigated for that purpose in an iris recognition system. A specific implementation of the multi-part architecture is proposed and the effect of the number of parts and samples in the resultant detection error rate is analysed. The effectiveness of the proposed architecture is then evaluated under two specific cases of obfuscation attack: miosis and mydriasis. Results show that robustness to such obfuscation attacks is achieved, since lower error rates than in the case of the non-fused base system are obtained.
Year
Venue
Keywords
2013
2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS)
iris recognition,image fusion
Field
DocType
Citations 
Computer vision,Iris recognition,Mydriasis,Image fusion,Decision fusion,Computer science,Word error rate,Robustness (computer science),Artificial intelligence,Biometrics,Obfuscation
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Tomeo-Reyes, I.174.86
Vinod Chandran251461.49