Iris image classification approach based on Dempster-Shafer theory of evidence

In order to improve the iris image classification rate, an image classification method is developed based on Dempster-Shafer evidence theory. Firstly, the ratio features of iris gray signals are extracted by using the texture changing information of iris images. Secondly, the decision classification is realized by employing Dempster-Shafer evidence theory to reduce the influence of uncertain factors on image classification and improve the classification rate. Under the same conditions, experiment validation has been carried out for various numbers of iris images, the results show that comparing with the histogram intersection and histogram ratio feature classification, the classification rate of the proposed algorithm is increased 6.96% and 4.44% respectively, while keeping the stability of classification.