An Iris Recognition Algorithm Based on Multi-feature Fuzzy Inference
Ke Li · Guangdian gongcheng · 2009
To get more representative iris features, three features, local feature point, local texture direction and changes between brightness and darkness of local texture are extracted through the gray-scale of iris images, which can depict the feature space of texture more fully and overcome the limitation of most previous algorithms which extract only susceptible single feature.Then patterns are categorized by the designed fuzzy inference regulation.The design of this piecewise linear classifier enhances the ability of linear classification of the algorithm.Experiments are implemented in two databases, respectively.The correct recognition rate is 99.41% and 99.67%, which demonstrate that many kinds of features can represent the variation details in the iris patterns properly.Therefore, the correctness is improved and the algorithm wins predominant recognition performance.