Genetic algorithm based feature selection level fusion using fingerprint and iris biometrics
Küçük Resim Yok
Tarih
2008
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
WORLD SCIENTIFIC PUBL CO PTE LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
An accuracy level of unimodal biometric recognition system is not very high because of noisy data, limited degrees of freedom, spoof attacks etc. problems. A multimodal biometric system which uses two or more biometric traits of an individual can overcome such problems. We propose a multimodal biometric recognition system that fuses the fingerprint and iris features at the feature extraction level. A feed-forward artificial neural networks (ANNs) model is used for recognition of a person. There is a need to make the training time shorter, so the feature selection level should be performed. A genetic algorithms (GAs) approach is used for feature selection of a combined data. As an experiment, the database of 60 users, 10 fingerprint images and 10 iris images taken from each person, is used. The test results are presented in the last stage of this research.
Açıklama
Anahtar Kelimeler
multibiometric, feature selection, genetic algorithms, artificial neural networks
Kaynak
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
22
Sayı
3
