Title :
Iris classification using WinICC and LAB color features
Author :
Pavaloi, I. ; Ciobanu, Amelia ; Luca, Mihaela
Author_Institution :
Inst. of Comput. Sci., Iaşi, Romania
Abstract :
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.
Keywords :
feature extraction; image classification; image colour analysis; image segmentation; iris recognition; software packages; visual databases; LAB color feature vectors; UBIRISv1 Internet available database; WinICC features; WinICC software package; classification test; color distribution; feature vectors; image classification; image clusterization; iris classification; iris image component extraction; iris image segmentation; k-NN feature; Image color analysis; Image segmentation; Iris; Support vector machine classification; Training; Vectors; LAB color features; SVM; clusterization; iris identification; k-NN;
Conference_Titel :
E-Health and Bioengineering Conference (EHB), 2013
Conference_Location :
Iasi
Print_ISBN :
978-1-4799-2372-4
DOI :
10.1109/EHB.2013.6707272
