Neural network based recognition by using Genetic algorithm for feature selection of enhanced fingerprints
Küçük Resim Yok
Tarih
2007
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SPRINGER-VERLAG BERLIN
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In order to ensure that the performance of a fingerprint recognition system will be powerful with respect to the quality of input fingerprint images, the enhancement of fingerprints is essential. In this study wavelet transform and contourlet transform which is a new extension of the wavelet transform in two dimensions are applied for fingerprint enhancement. In addition, feature selection is a process that chooses a subset of features from the original fingerprint features so that the feature space is optimally reduced according to a certain criterion. In this study, a Genetic Algorithms (GAs) approach to fingerprint feature selection is proposed and selected features are input to Artificial Neural Networks (ANNs) for fingerprint recognition. The performance has been tested on fingerprint recognition.
Açıklama
8th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA) -- APR 11-14, 2007 -- Warsaw Univ Technol, Warsaw, POLAND
Anahtar Kelimeler
Kaynak
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS, PT 2
WoS Q Değeri
N/A
Scopus Q Değeri
Q3
Cilt
4432
