Abstract
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Article Information:
Multimodal Biometrics Based on Fingerprint and Finger Vein
Anand Viswanathan and S. Chitra
Corresponding Author: Anand Viswanathan
Submitted: March 22, 2014
Accepted: April 28, 2014
Published: July 10, 2014 |
Abstract:
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Biometric systems identify a person through physical traits or verify his/her identity through automatic processes. Various systems were used over years including systems like fingerprint, iris, facial images, hand geometry and speaker recognition. For biometric systems successful implementation, it has to address issues like efficiency, accuracy, applicability, robustness and universality. Single modality based recognition verifications are not robust while combining information from different biometric modalities ensures better performance. Multimodal biometric systems use multiple biometrics and integrate information for identification. It compensates unimodal biometric systems limitations. This study considers multimodal biometrics based on fingerprint and finger veins. Gabor features are extracted from finger vein using Gabor filter with orientation of 0, 15, 45, 60 and 75°, respectively. For fingerprint images, energy coefficients are attained using wavelet packet tree. Both features are normalized using min max normalization and fused with concatenation. Feature selection is through PCA and kernel PCA. Classification is achieved through KNN, Naïve Bayes and RBF Neural Network Classifiers.
Key words: Biometric systems, Gabor filter, K-Nearest Neighbors (KNN), naïve bayes and Radial Basis Function (RBF) neural network classifier, Principal Component Analysis (PCA), ,
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Cite this Reference:
Anand Viswanathan and S. Chitra, . Multimodal Biometrics Based on Fingerprint and Finger Vein. Research Journal of Applied Sciences, Engineering and Technology, (2): 226-234.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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