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A Frequency Based Approach on Biometric Identification System Using Multiple Traits of Face and Iris

C.B. Rublin Bini, C. Anand Deva Durai

Abstract


In the modern era, biometric identification place an
important role to identify humans in a unique manner. Single or multiple physical traits can be used in various applications. Single Biometric traits face problems such as poor environment, nonuniversality, noisy data. To overcome these, multimodal biometric identification uses more than one physical trait so that it increases the performance in identification which is not possible in single
biometric system. Also, it is difficult for the intruder to
simultaneously spoof the multiple traits. This paper uses face and iris as multiple physical traits. To extract the features of face and iris Local Binary Pattern is used and phase only correlation for latter. The fusion of features is done using frequency based fusion where Log Gabor filter is used in matching score level.


Keywords


Feature Extraction, Local Binary Pattern, Feature Fusion, Hamming Distance.

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References


Hua Gu,Guangda Su, Cheng Du. Feature Points Extraction from faces.

Image and Vision Computinh NZ; p. 154-158; Nov.2003.

Peter N.Belhumeur, Joao P. Hespanha, David J. Kriegman. Eigenfaces

vs Fisherfaces: Recognition Using Class Specific Linear Projection.

IEEE Transactions on Pattern Analysis and Machine Intelligence.age.

VOl.19; p. 711-719; July.1997.

Lindsay I Smith. A tutorial on Principlal Component Analysis. ISBN: 0-

-8344-9;Feb.2002.

Heng Fui Liau, Dino Isa.Feature selection for support vector machinebased

face-iris multimodal biometric syatem. Expert systems with

Applications. VOl.38; p. 11105-11111; 2011.

Kuzuyuki Miyazawa, Koichi Ito, Takafumi Aoki, Koji Kobayshi,

Hiroshi Nakajima. An effective approach for Iris recognition using

Phase-Based Image Matching. IEEE Transactions on Pattern Analysis

and Machine Intelligence.age. VOl.30; p. 1741-1755;Oct.2008.

V.C. Subbarayudu, M.V. N. K. Prasad. Multimodal Biometric System.

In Proc. Ist nt. IEEE Conf. Emerging Trends Eng. Technol. p. 635-640;

DOI 10.1109/ICETET;2008. 93.

Timo Ahonen, Abdenour Hadid,Matti Pietikainen. Face Describtion

with Local Binary Patterns: Application to face Recognition. IEEE

Transactions on pattern analysis and machine Intelligence.June.2006.

Vincenzo Conti, Carnelo Militello, Filippo Sorbello. A Frequency based

Approach for Features Fusion in Fingerprint and Iris Mltimodal

Biometric Identification Systems..IEEE Transcations on systems, man,

and Cybernetics; VOl.40; July.2010.

A.B. Khalifa and N.E.B. Amara, Bimodal biometric verification with

different fusion levels. Multi-Conf. Syst.,Signal Devices. p. 1-6; DOI:

1109/SSD. 2009.4956731.

Fitri Arnia, Nuriza Pramita. Enhancement of Iris Recognition System

based on Phase Only Correlation. Telkomnika. VOL.9; p. 387-394;

August 2011.


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