In this article, we present a novel probabilistic iris quality measure based on a Gaussian Mixture Model (GMM). We compare its behavior to that of other standard iris quality metrics on two different types of noise which can corrupt the iris texture: occlusions and blurring. In the case of occlusions, we compare our GMM-based quality measure to an active contour method for eyelids and eyelashes detection. Finally, in the case of iris blurring, we compare our quality measure to a standard method based on Fourier Transform and wavelets. For the latter, we have developed a new method to detect blur suitable for iris images. In our tests, we have used the ICE 2005 database and OSIRIS, an iris reference system based on the classical approach proposed by Daugman and developed in the framework of BioSecure European Network of Excellence for comparative evaluation purposes. Experiments show a significant improvement of performance when our GMMbased quality measure is used instead of the classical methods above mentioned. In particular, results show that this probabilistic quality measure based on a GMM trained on good quality images is independent from the kind of noise involved.
Abstract. In this paper we propose a novel iris recognition method for iris images acquired under normal light illumination. We exploit the color information as we compare the distributions of common colors between a reference image and a test image using a modified Hausdorff distance. Tests have been made on the UBIRIS public database and on the IRIS_INT database acquired by our team. Comparisons with two iris reference systems in controlled scenario show a significant improvement when using color information instead of texture information. On uncontrolled scenarios, we propose a quality measure on colors in order to select good images from bad ones in the comparison process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.