Robust Iris Segmentation under Unconstrained Settings

• Type: Article in International Conference Proceedings Book
• Date: 2013

Authors

Monteiro, JC (Author) Other; Oliveira, HP (Author) FEUP; Sequeira, AF (Author) Other; Cardoso, JS (Author) FEUP

Conference proceedings International

Title: VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications

Pages: 180-190

8th International Conference on Computer Vision Theory and Applications, VISAPP 2013

Barcelona, 21 February 2013 through 24 February 2013

Indexing

ISI Web of Knowledge

Scopus - 7 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-008-B5K

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific