Iris recognition using statistics on pixel position

In this paper we present experiments made on an extension of a well-known simple global color criterion and we present the results obtained in iris recognition on two known iris databases, UBIRIS and UPOL. All tests were done for three different color spaces, RGB, HSV and LAB, and two discriminative classifiers, k-NN (k - Nearest Neighborhood) and SVM (Support Vector Machine) were used in our experiments. For the k-NN, three classic distances, Canberra, Euclidean and Manhattan and other two new distances we proposed were used in experiments. The results obtained using the extension color criterion are compared with the ones obtained with the original criterion.