This paper presents a robust method for iris segmentation. To detect the inner boundary of the iris, the method introduces a circular filter, which is specially designed to detect circular shapes in iris images. The inner boundary detection process consists of two steps. First, the coarse center of the pupil is detected via the proposed filter. Then, a set of inner boundary points is found by using the Radon transform to detect segment lines in the rectangular areas, which are converted from extracted arc regions with the coarse center. The inner boundary is finally determined by fitting the set of points to a circle using the least-mean-squares method. In addition, the proposed method includes a process for extracting the outer boundary of the iris by applying a linear filter to the rectangular areas transformed from arc regions around the iris. Furthermore, a fast method for detecting eyelids after iris segmentation is presented. Experimental results over the CASIA iris databases show that the performance of the proposed methods is promising for iris images captured in unconstrained environments.