Authors:
João C. Monteiro
;
Hélder P. Oliveira
;
Ana F. Sequeira
and
Jaime S. Cardoso
Affiliation:
Universidade do Porto, Portugal
Keyword(s):
Biometrics, Iris Segmentation, Unconstrained Environment, Gradient Flow, Shortest Closed Path.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
The rising challenges in the field of iris recognition, concerning the development of accurate recognition
algorithms using images acquired under an unconstrained set of conditions, is leading to the a renewed interest
in the area. Although several works already report excellent recognition rates, these values are obtained by
acquiring images in very controlled environments. The use of such systems in daily security activities, such
as airport security and bank account management, is therefore hindered by the inherent unconstrained nature
under which images are to be acquired. The proposed work focused on mutual context information from iris
centre and iris limbic contour to perform robust and accurate iris segmentation in noisy images. A random
subset of the UBIRIS.v2 database was tested with a promising E1 classification rate of 0.0109.