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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)
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)
Finger vein recognition is a biometric technique which identifies individuals using their unique finger vein patterns. It is reported to have a high accuracy and rapid processing speed. In addition, it is impossible to steal a vein pattern located inside the finger. We propose a new identification method of finger vascular patterns using a weighted local(More)
Although iris recognition technology has been reported to be more stable and reliable than other biometric systems, performance can be degraded due to many factors such as small eyes, camera defocusing, eyelash occlusions and specular reflections on the surface of glasses. In this paper, we propose a new multi-unit iris authentication method that uses score(More)
— Iris recognition is a form of biometric techniques that identifies user with the unique iris patterns between the pupil and the sclera. There is an advantage that its recognition accuracy is very high due to high DOF (degree of freedom) of the iris patterns. However, it requires an iris image with high quality in order to preserve the high recognition(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)