DocumentCode :
2224249
Title :
A comparison of GEC-based feature selection and weighting for multimodal biometric recognition
Author :
Alford, Aniesha ; Popplewell, Khary ; Dozier, Gerry ; Bryant, Kelvin ; Kelly, John ; Adams, Josh ; Abegaz, Tamirat ; Shelton, Joseph ; Ricanek, Karl ; Woodard, Damon L.
Author_Institution :
Center for Adv. Studies in Identity Sci., North Carolina A & T State Univ., Greensboro, NC, USA
fYear :
2011
fDate :
5-8 June 2011
Firstpage :
2725
Lastpage :
2728
Abstract :
In this paper, we compare the performance of a Steady-State Genetic Algorithm (SSGA) and an Estimation of Distribution Algorithm (EDA) for multi-biometric feature selection and weighting. Our results show that when fusing face and periocular modalities, SSGA-based feature weighting (GEFeWSSGA) produces higher average recognition accuracies, while EDA-based feature selection (GEFeSEDA) performs better at reducing the number of features needed for recognition.
Keywords :
biometrics (access control); distributed algorithms; feature extraction; genetic algorithms; EDA; GEC; SSGA; estimation of distribution algorithm; feature selection; feature weighting; multimodal biometric recognition; steady-state genetic algorithm; Accuracy; Face; Face recognition; Feature extraction; Iris recognition; Probes; Eigenface; Estimation of Distribution Algorithm; Feature Selection; Feature Weighting; Local Binary Pattern; Steady-State Genetic Algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
ISSN :
Pending
Print_ISBN :
978-1-4244-7834-7
Type :
conf
DOI :
10.1109/CEC.2011.5949959
Filename :
5949959
Link To Document :
https://search.ricest.ac.ir/dl/search/defaultta.aspx?DTC=49&DC=2224249
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