The first step in finding the actual iris radius is to find an approximation of the iris radius. This approximation can then be fine tuned to find the actual iris parameters. In order to find this approximation a single edge of the iris must be found. Knowing that eyes are most likely to be distorted in the top and bottom parts due to eyelashes and eyelids, the best choice for finding an unobstructed edge is along the horizontal line through the pupil center.

Having decided on where to attempt to detect the iris edge, the question of how to do it arises. It seems obvious that some type of edge detection should be used. It happens that for any edge detection it is a good idea to blur the image to subtract any noise prior to running the algorithm, but too much blurring can dilate the boundaries of an edge, or make it very difficult to detect. Consequently, a special smoothing filter such as the median filter should be used on the original image. This type of eliminates sparse noise while preserving image boundaries. The image may need to have its contrast increased after the median filter.

Now that the image is prepped the edge detection can be done. Since there is such a noticeable rising edge in luminescence at the edge of the iris, filtering with a haar wavelet should act as a simple edge detector. The area of interest is not just the single horizontal line through the iris, but the portion of that line to the left of the pupil. This is so that the rising luminescence from the transition from iris to white is the only major step.

The iris should represent the steepest luminence change in the area of interest. Consequently, this area of the image should correspond to the highest valued componenet of the the output from the filter. By finding this maximal value the edge of the iris to the right of the pupil should be found. It should be noted that since the iris may not be concentric with the pupil the distance from the pupil center to this edge may not correspond to the iris' radius.