GEC-based multi-biometric fusion

Aniesha Alford; Caresse Hansen; Gerry Dozier; Kelvin Bryant; John Kelly; Tamirat Abegaz; Karl Ricanek; Damon L. Woodard

doi:10.1109/cec.2011.5949870

GEC-based multi-biometric fusion

Aniesha Alford
, Caresse Hansen
, Gerry Dozier
, Kelvin Bryant
, John Kelly
, Tamirat Abegaz
, Karl Ricanek
, Damon L. Woodard

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we use Genetic and Evolutionary Computation (GEC) to optimize the weights assigned to the biometric modalities of a multi-biometric system for score-level fusion. Our results show that GEC-based multi-biometric fusion provides a significant improvement in the recognition accuracy over evenly fused biometric modalities, increasing the accuracy from 90.77% to 95.24%. © 2011 IEEE.

Original language	English
Title of host publication	2011 IEEE Congress of Evolutionary Computation, CEC 2011
DOIs	https://doi.org/10.1109/cec.2011.5949870
State	Published - 2011

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10.1109/cec.2011.5949870

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@inproceedings{a9ac84fbad0d4b0884e75916b87632c2,

title = "GEC-based multi-biometric fusion",

abstract = "In this paper, we use Genetic and Evolutionary Computation (GEC) to optimize the weights assigned to the biometric modalities of a multi-biometric system for score-level fusion. Our results show that GEC-based multi-biometric fusion provides a significant improvement in the recognition accuracy over evenly fused biometric modalities, increasing the accuracy from 90.77\% to 95.24\%. {\textcopyright} 2011 IEEE.",

author = "Aniesha Alford and Caresse Hansen and Gerry Dozier and Kelvin Bryant and John Kelly and Tamirat Abegaz and Karl Ricanek and Woodard, \{Damon L.\}",

year = "2011",

doi = "10.1109/cec.2011.5949870",

language = "English",

booktitle = "2011 IEEE Congress of Evolutionary Computation, CEC 2011",

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T1 - GEC-based multi-biometric fusion

AU - Alford, Aniesha

AU - Hansen, Caresse

AU - Dozier, Gerry

AU - Bryant, Kelvin

AU - Kelly, John

AU - Abegaz, Tamirat

AU - Ricanek, Karl

AU - Woodard, Damon L.

PY - 2011

Y1 - 2011

N2 - In this paper, we use Genetic and Evolutionary Computation (GEC) to optimize the weights assigned to the biometric modalities of a multi-biometric system for score-level fusion. Our results show that GEC-based multi-biometric fusion provides a significant improvement in the recognition accuracy over evenly fused biometric modalities, increasing the accuracy from 90.77% to 95.24%. © 2011 IEEE.

AB - In this paper, we use Genetic and Evolutionary Computation (GEC) to optimize the weights assigned to the biometric modalities of a multi-biometric system for score-level fusion. Our results show that GEC-based multi-biometric fusion provides a significant improvement in the recognition accuracy over evenly fused biometric modalities, increasing the accuracy from 90.77% to 95.24%. © 2011 IEEE.

UR - https://dx.doi.org/10.1109/CEC.2011.5949870

U2 - 10.1109/cec.2011.5949870

DO - 10.1109/cec.2011.5949870

M3 - Conference contribution

BT - 2011 IEEE Congress of Evolutionary Computation, CEC 2011

ER -

GEC-based multi-biometric fusion

Abstract

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