Authentication Based on Finger Vein Recognition Using Neuro-Fuzzy Technique
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Date
2015
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Abstract
vlany computational problems are achieved by Artificial
ntelligence which is based on mathematical equations and
irtifid-'i neurons. The main focus is on the implementation of
Inge in recognition for personal authentication. Basically
he finger vein patterns are captured by a device that can
ransmit near infrared through the finger and record the
jatterns. The proposed biometric system for verification
lonsist of a combination of feature extraction using Genetic
Principal Component Analysis(GPCA) technique to obtain the
iptimized features and pattern classification using Neuromzzy
technique which is a learning algorithm. To verify the
Tfect of the proposed Neuro fuzzy system in the pattern
ilassification, the Back Propagation Network(BPN) is
lompared with the proposed system. The experimental results
ndicated the proposed system using Neuro fuzzy has better
rerformance than the BPN for personal identification using
he finger-vein patterns. This paper shows the finger vein
ramework with the parameter of false acceptance rate (FAR),
alse rejection rate (FRR) and total execution time for the
lystem.