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General Information
    • ISSN: 2010-3719 (Online)
    • Abbreviated Title: Int. J. Inf. Electron. Eng.
    • Frequency: Quarterly
    • DOI: 10.18178/IJIEE
    • Editor-in-Chief: Prof. Chandratilak De Silva Liyanage
    • Executive Editor: Jennifer Zeng
    • Abstracting/ Indexing : Google Scholar, Electronic Journals Library, Crossref and ProQuest, Ei (INSPEC, IET), EBSCO.
    • E-mail ijiee@ejournal.net

University of Brunei Darussalam, Brunei Darussalam   
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IJIEE 2011 Vol.1(1): 52-58 ISSN: 2010-3719
DOI: 10.7763/IJIEE.2011.V1.8

Prodigious Utilization of Genetic Algorithm in Tuning Gabor filter parameters in the Application of Iris Recognition

Yogesh Karunakar

Abstract—Gabor filters find an important place in image processing field but the use is restricted because of its computational complexity. Many methods are used in practice for security systems. Most common being the face recognition, voice recognition and biometric methods. Biometric systems are finding a lot of acceptances in the market. Mostly the finger print recognition and the iris recognition. Accurate automatic personal identification is critical in a variety of applications in our electronically interconnected society. Biometrics, which refers to identification based on physical or behavioral characteristics, is being increasingly adopted to provide positive identification with a high degree of confidence. Among all the biometric techniques, IRIS based authentication systems have received the most attention because of the uniqueness of iris. Due to its reliability and nearly perfect recognition rates, iris recognition is used in high security areas In this paper, a systematic approach is introduced to design the parameters of the Gabor filter banks for iris recognition. In this paper we also introduce how the Genetic Algorithm (GA) can be used to tune the parameters of the Gabor filter banks. The paper also explains how Daugman’s method can be used from a different point of view. We have also tried to show how Gabor filters can be replaced by a different set of filters, i.e., the Derivative of Gaussian (DoG) and the Laplacian of Gaussian (LoG) without sacrificing the recognition rate.

Index Terms—Daugman’s method, Derivative Of Gaussian(DOG),Genetic Algorithm, Gabor Filter, Iris Recognition, Laplacian Of Gaussian (LOG).

Yogesh Karunakar is with the Shree L. R. Tiwari College of Engineering, Mira Road, India (phone: +91-9594276600; e-mail: askyogi@gmail.com).


Cite: Yogesh Karunakar, "Prodigious Utilization of Genetic Algorithm in Tuning Gabor filter parameters in the Application of Iris Recognition," International Journal of Information and Electronics Engineering vol. 1, no. 1, pp. 52-58, 2011.

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