In this paper, we describe a new method for detecting iris in digital images. Our method is simple yet effective. It is based on statistical point of view when searching for limbic boundary and rather analytical approach when detecting pupillary boundary. It can be described in three simple steps; firstly, the bright point inside the pupil is detected; secondly, outer limbic boundary is found via statistical measurements of outer boundary points; and thirdly, inner boundary points are found by means of defined cost function maximization. Performance of the presented method is evaluated on series of iris close-up images and compared with the traditional Hough method as well.