Fast pupil location for better iris detection

The inner edge of the iris corresponds to the pupil one. Thus, it is enough to locate as precisely as possible the latter to delimit the iris inner side. The distinguished gray levels within the pupil can be very useful in its localization task. Indeed, this area often appears as the darkest one in the image. Therefore, by studying the gray level distribution in the image, one can locate the pupil as the whole of pixels that have the least gray levels. This can be ensured by histogram thresholding. However by using such a technique, the localized pupil is threatened to be perforated, in case of presence of reflection points, or deformed by the addition of noisy elements such as lashes and dark textons. In this paper, a morphological cleaning technique is used to clear out the pupil binary image. This pupil localization strategy makes it possible to accurately delimit the iris by the interior, as well as it estimates pupil center that approximately provides us the iris one. Using this strategy before applying the integro-differential operator, the Hough transform algorithm or the multi scale edge detector approach, a near 18 times faster localization of iris is achieved.