Segmentation of non-ideal iris image based on statistical features
Wan Hong-li · Journal of Optoelectronics·laser · 2013
Since the presence of the degraded conditions such as illuminative variations,eyelashes or eyelids occlusions,ambiguous outer boundary,etc,the key of recognition for non-ideal iris in real application is to correctly segment iris region which contains texture features distinguishing aperson from another.In this paper,we propose the segmentation method for non-ideal iris based on statistical features of images.It consists of three phases,i.e.,inner boundary localization,outer boundary localization,and eyelids detection.In inner boundary localization,this method localizes pupil and iris center accurately by exploiting Gaussian mixture model(GMM)and multiple strings equilibrium.By GMM,multiple Gaussian distributions are evolved to fit image histogram.For this reason,GMM is adaptive among iris images in different databases.In outer boundary localization,we present the simplified region-based curve evolution which is combined with order statistical filters(OSFs)to guarantee its convergence to exterior iris boundary.Finally in eyelids detection we employ parabola to model iris eyelids.By evaluating the databases,this method can segment non-ideal iris accurately by eliminating undesirable reflections and eyelash/eyelid occlusions.