• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.592-595
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• 2004

Recently the numbers of patent about the technology for mobile payment with Ie or bluetooth-chip are being increased more and more. The reasons of patent increment for mobile payment are advancement of wireless internet technology and rising of customer's request for it. The customer wants to be able to pay for purchase, tax and aid with own mobile phone. So every mobile service provider applies for patents about that competitively. And in the near future the biometrics is generalized in the mobile payment system. Especially the payment service of iris recognition is significant technique in this area for the future prospect. The biometrics of iris is an accurate authentication method because it has about 250 distinguish parameters to the finger print's 30. The biometrics of iris can recognize and identify a person for 2 seconds. But the image of iris is changed by transformation of body in the life. And the existing iris authentication system has problem that can be miss-recognized. In this paper, we propose the new method that reduces miss-recognizing rate with Renewable Iris Authentication Algorithm(RIAA) in mobile system.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.876-884
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• 2003

It is essential to identify both the pupil and iris boundaries for iris recognition. The circular edge detector proposed by Daugman is the most common and powerful method for the iris region extraction. The method is accurate but requires lots of computational time since it is based on the exhaustive search. Some heuristic methods have been proposed to reduce the computational time, but they are not as accurate as that of Daugman. In this paper, we propose a pupil and iris boundary finding algorithm which is faster than and as accurate as that of Daugman. The proposed algorithm searches the boundaries using the Daugman's circular edge detector, but reduces the search region using the problem domain knowledge. In order to find the pupil boundary, the search region is restricted in the maximum and minimum bounding circles in which the pupil resides. The bounding circles are obtained from the binarized pupil image. Two iris boundary points are obtained from the horizontal line passing through the center of the pupil region obtained above. These initial boundary points, together with the pupil point comprise two bounding circles. The iris boundary is searched in this bounding circles. Experiments show that the proposed algorithm is faster than that of Daugman and more accurate than the conventional heuristic methods.