Texture Descriptor Extraction for Iris Classification using Fuzzy Logic Local Binary Pattern

Feature extraction in the iris classification field is an essential stage that is applied to produce a discriminative descriptor for each subject. Uncertainty due to contrast and other noises may degrade the exactness of descriptors between subject. In achieving to tackle the problem, fuzzy logic local binary pattern concept that uses a specific rule to decide the uncertainty intensity values between central and neighboring pixels has been applied for feature extraction. An experimental setup has been performed to evaluate the concept using two freely available databases which are CASIA V3 and IITD. A promising result with more than 98% of the classification score success rate has achieved by using Support Vector Machines classifier.