Iris Recognition Using Ridgelets

Lenina Birgale and Manesh Kokare
Volume: 8, No: 3, Page: 445 ~ 458, Year: 2012
10.3745/JIPS.2012.8.3.445
Keywords: Ridgelets, Texture, Wavelets, Biometrics, Features, Database
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Abstract
Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.

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Cite this article
IEEE Style
Lenina Birgale and Manesh Kokare, "Iris Recognition Using Ridgelets," Journal of Information Processing Systems, vol. 8, no. 3, pp. 445~458, 2012. DOI: 10.3745/JIPS.2012.8.3.445.

ACM Style
Lenina Birgale and Manesh Kokare, "Iris Recognition Using Ridgelets," Journal of Information Processing Systems, 8, 3, (2012), 445~458. DOI: 10.3745/JIPS.2012.8.3.445.