DocumentCode
3647823
Title
Model-based pupil and iris localization
Author
Nitin K. Mahadeo;Andrew P. Papliński;Sid Ray
Author_Institution
Clayton School of Information Technology, Monash University, Australia
fYear
2012
fDate
6/1/2012 12:00:00 AM
Firstpage
1
Lastpage
7
Abstract
The iris is the most accurate biometric to date and its localization is a vital step in any iris recognition system. Iris localization can be considered as the search for the demarcation points, or step change in intensity at its boundaries. A failed localization will lead to incorrect iris segmentation and eventually to poor recognition. In the first stage, we proceed with the elimination of reflection and the reduction of lighting variations in eye images. In the second stage of our proposed system, radii and locations of the pupil and iris are obtained by maximizing the convolution of the image with a toroidal 2-D filtering shape derived from the Petrou-Kittler 1-D filter. Such a novel approach delivers robust localization of the inner and outer iris boundaries. We tested our system on a large dataset of poor quality eye images with substantial occlusions, illumination and defocus and the proposed algorithm is found to be robust and accurate.
Keywords
"Iris","Iris recognition","Lighting","Image edge detection","Convolution","Image segmentation","Shape"
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2012 International Joint Conference on
ISSN
2161-4393
Print_ISBN
978-1-4673-1488-6
Type
conf
DOI
10.1109/IJCNN.2012.6252562
Filename
6252562
Link To Document