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Many researchers have studied iris recognition techniques in unconstrained environments, where the probability of acquiring non-ideal iris images is very high due to off-angles, noise, blurring and occlusion by eyelashes, eyelids, glasses, and hair. Although there have been many iris segmentation methods, most focus primarily on the accurate detection with(More)
In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower(More)
A new iris recognition method for mobile phones based on corneal specular reflections (SRs) is discussed. We present the following three novelties over previous research. First, in case of user with glasses, many noncorneal SRs may happen on the surface of glasses and it is very difficult to detect genuine SR on the cornea. To overcome such problems, we(More)
When capturing an iris image under unconstrained conditions and without user cooperation, the image quality can be highly degraded by poor focus, off-angle view, motion blur, specular reflection (SR), and other artifacts. The noisy iris images increase the intra-individual variations, thus markedly degrading recognition accuracy. To overcome these problems,(More)