WIRE: Watershed based iris recognition. (April 2016) - Frucci, Maria; Nappi, Michele; Riccio, Daniel; Sanniti di Baja, Gabriella
Abstract: A Watershed transform based Iris REcognition system (WIRE) for noisy images acquired in visible wavelength is presented. Key points of the system are: the color/illumination correction pre-processing step, which is crucial for darkly pigmented irises whose albedo would be dominated by corneal specular reflections; the criteria used for the binarization of the watershed transform, leading to a preliminary segmentation which is refined by taking into account the watershed regions at least partially included in the best iris fitting circle; the introduction of a new cost function to score the circles detected as potentially delimiting limbus and pupil. The advantage offered by the high precision of WIRE in iris segmentation has a positive impact as regards the iris code, which results to be more accurately computed, so that the performance of iris recognition is also improved. To assess the performance of WIRE and to compare it with the performance of other available methods, two well known databases have been used, specifically UBIRIS version 1 session 2 and the subset of UBIRIS version 2 that has been used as training set for the international challenge NICE II. Highlights: Iris segmentation from visible images captured in uncontrolled conditions often fails. The watershed transform is used to detect the limbus. Cumulative sums can be used to perform iris recognition.