Transformation based Score Fusion Algorithm for Multi-modal Biometric User Authentication through Ensemble Classification | Zendy

Firas Souhail Assaad | Zendy; Gürsel Serpen | Zendy

Open Access

Transformation based Score Fusion Algorithm for Multi-modal Biometric User Authentication through Ensemble Classification

Author(s) -

Firas Souhail Assaad,

Gürsel Serpen

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.09.175

Subject(s) - computer science , biometrics , modal , classifier (uml) , transformation (genetics) , fusion , authentication (law) , artificial intelligence , pattern recognition (psychology) , algorithm , speech recognition , biochemistry , chemistry , linguistics , philosophy , computer security , polymer chemistry , gene

This paper presents a simulation study for a fusion or combiner algorithm for an ensemble classifier, which facilitates multi-modal biometric user authentication. The study employs the transformation-based score fusion method with the voice and face recognition classifier outputs as inputs. This fusion technique is only dependent on the score generated from each biometric module. The simulation study was conceived to show the feasibility, utility and application of the transformation-based score fusion algorithm. The simulation scenario entails users registering, training, and authenticating through their voice recordings and face images. Performance of the authentication system based on the proposed fusion algorithm indicated that the true positive rate is 99.15%, and the true negative rate is 99.28%. Simulation results suggest that the proposed authentication system is feasible and its performance is promising for real-life applications

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