Research Of Iris Recognition Based On Feature Selection

Biometric technology deals with recognizing the identity of individuals based on their unique physical or behavioral characteristics. Physical characteristics such as fingerprint, palm print, hand geometry and iris patterns or behavioral characteristics such as typing pattern and hand-written signature present unique information about a person and can be used in authentication applications. Biometric technology has many desirable properties, such as unique, reliability, stability and so on. Among biometric systems, iris recognition is a kind of novel biometrics which was developed from 1990s and it has attracted more and more attention because of its high accuracy. Thanks to its complex structures and abundant features, the iris has many desirable properties, such as unique, stable, collectable, hard to be changed, non-intrusive, and so on.In this paper,a novel iris localization method and user-specific automatic iris authentication approach based on feature selection is proposed. First, two iris sub-regions, where are nearly not occluded by useless parts such as eyelash and eyelid, are segmented as region of interest (ROI). Second, multi-scale Gabor filters are adopted to extract the texture feature of ROI. Third, genetic algorithm (GA) and support vector machine (SVM) are employed for feature selection and classification. Through feature selection, each user has specific feature index and authentication modality.For proving the effectiveness and feasibility, we respectively in CASIA database has carried out an experiment verified Iris Authentication Based on Feature selection methods validity which this paper proposed. The experimental results show the proposed approach can achieve lower error rates in iris authentication.