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, we propose a new iris recognition algorithm for noisy

iris images.