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Abstract
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Article Information:
Optimized Radial Basis Function Classifier for Multi Modal Biometrics
Anand Viswanathan and S. Chitra
Corresponding Author: Anand Viswanathan
Submitted: March 29, 2014
Accepted: April 28, 2014
Published: July 25, 2014 |
Abstract:
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Biometric systems can be used for the identification or verification of humans based on their physiological or behavioral features. In these systems the biometric characteristics such as fingerprints, palm-print, iris or speech can be recorded and are compared with the samples for the identification or verification. Multimodal biometrics is more accurate and solves spoof attacks than the single modal bio metrics systems. In this study, a multimodal biometric system using fingerprint images and finger-vein patterns is proposed and also an optimized Radial Basis Function (RBF) kernel classifier is proposed to identify the authorized users. The extracted features from these modalities are selected by PCA and kernel PCA and combined to classify by RBF classifier. The parameters of RBF classifier is optimized by using BAT algorithm with local search. The performance of the proposed classifier is compared with the KNN classifier, Naïve Bayesian classifier and non-optimized RBF classifier.
Key words: BAT optimization, fingerprint, finger vein, local search, multimodal biometrics, Radial Basis Function (RBF) classifier,
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Cite this Reference:
Anand Viswanathan and S. Chitra, . Optimized Radial Basis Function Classifier for Multi Modal Biometrics. Research Journal of Applied Sciences, Engineering and Technology, (4): 521-529.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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