In this paper an iris detection scheme for noisy images acquired by means of mobile devices is presented. Iris segmentation is accomplished by exploiting the use of the watershed transform with the purpose of identifying the iris boundary as much precisely as possible. After a pre-processing step aimed at color/illumination correction, the watershed transform is computed and suitably binarized. Circle fitting is then accomplished to identify the limbus boundary by using curvature approximation and a cost function for circle scoring. The watershed transform is furthermore employed to distinguish, in the zone delimited by the best fitting circle, the regions actually belonging to the iris from those belonging to eyelids and sclera. Finally, pupil detection is accomplished by means of circle fitting and by using a voting function based on homogeneity and separability criteria. The suggested iris detection scheme has a positive impact on an the accuracy in computing the iris code, which has in turn a positive impact on the performance of iris recognition.