An Iris Recognition Algorithm Based on Principle Component Analysis and Independent Component Analysis
基于PCA和ICA的虹膜识别方法

A new iris recognition algorithm,based on PCA and ICA,is proposed in this paper.Firstly,PCA was applied to the iris images in order to reduce dimension and second order correlation,then ICA was applied to train iris images.In our algorithm,ICA was performed on iris images in the CASIA database under two different architectures,of which one treated the image as random variables and the pixels as outcomes,while the other treated the pixels as random variables and the images as outcomes.The first architecture found spatially independent basis images for the iris.The second architecture used ICA to find a representation in which the coefficients used to code images were statistically independent.No matter which architecture we used to train the iris images,the proposed algorithm was effective.