Iris segmentation is the most determining factor in iris biometrics, which has traditionally assumed rigid constrained environments. In this work, a novel method that covers the localization of the pupillaty and limbic iris bound- aries is proposed. The algorithm consists of an energy minimization procedure posed as a multilabel one-directional graph and the use of physiological priors, achieving accurate segmentations even in the presence of clutter, lenses, glasses, motion blur, and variable illumination. The contributions of this paper are a fast and reliable method for the accurate localization of the iris boundaries in low- constrained conditions, which has been evaluated over two public databases, and a new database for iris segmentation incorporating challenging iris images, which has been publicly released to the research community