Iris classification using WinICC and LAB color features
Ioan Păvăloi, Adrian Ciobanu, Mihaela Luca · 2013
We present the WinICC software package, designed to help in tasks like clusterization or classification of images based on different feature vectors. The capabilities of this software are proven on a classification test involving 1.205 already segmented iris images belonging to 241 persons (five iris images per person - part of the UBIRISv1 Internet available database). We used the k-NN feature of the WinICC applied on LAB color feature vectors with 80 components extracted from iris images. The resulted rates of correctly classified irises are over 88% if 3 or 4 images are used to classify the remaining images of the same person. As the data set is not perfect, this is a result that may suggest a possible identification of human irises based on color distribution.