As you are probably aware, during 2007-2009 the SOCIA Lab. (Soft Computer And Image Analysis Group, University of Beira Interior, Portugal) held an international contest for iris biometric purposes. It focused on the segmentation and noise detection of iris images captured in the visible wavelength and under unconstrained imaging setups. This contest (NICE.I - Noisy Iris Challenge Evaluation, received over 90 participations from over 20 different countries and the best 8 participants were invited to publish their method in a special issue of the Image and Vision Computing Journal (IVC, to appear in 2010). Now, we are organizing the complementary part of the contest (NICE:II) that will comprise the signatures encoding and matching of previously segmented noisy iris images. This will complete the evaluation of the most traditional stages of iris recognition systems: segmentation + noise detection (NICE.I, IVC Special Issue) and signatures encoding + matching (NICE:II, Pattern Recognition Letters Special Issue). Once again, the idea is to publish a special issue describing the best 8 to 10 methods of the contest, which hopefully will constitute an important step toward the development of less constrained iris recognition systems. We have already developed the software for the automatic evaluation of the participations and the web page with the most important information is online (please, check more information at Briefly, the NICE:II is a completely free-of-charge iris encoding and matching contest that operates on noisy data acquired under less constrained image conditions and in the visible wavelength. As before stated, the participations that achieve the lowest error rates will be invited to publish their approach in the Pattern Recognition Letters Journal, (ISI Web-of-Knowledge indexed), in the NICE:II special issue. Detailed information can be found at the contest web site: We look forward for your participation. You are also invited to propose the participation in the NICE:II to undergraduated, MSc. or PhD. students under your supervision.