Iris classification using WinICC and LAB color features

Author

Pavaloi, I. ; Ciobanu, Amelia ; Luca, Mihaela

Author_Institution

Inst. of Comput. Sci., Iaşi, Romania

fYear

2013

fDate

21-23 Nov. 2013

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

E-Health and Bioengineering Conference (EHB), 2013

Conference_Location

Iasi

Print_ISBN

978-1-4799-2372-4

Type

conf

DOI

10.1109/EHB.2013.6707272

Filename

6707272