An Investigation of Quality Aspects of Noisy Colour Images for Iris Recognition

McConnon, G. and Deravi, Farzin and Hoque, Sanaul and Sirlantzis, Konstantinos and Howells, Gareth (2011) An Investigation of Quality Aspects of Noisy Colour Images for Iris Recognition. International Journal of Signal Processing, Image Processing and Pattern Recognition, 4 (3). pp. 165-178. ISSN 2005-4254. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not available from this repository. (Contact us about this Publication)


The UBIRIS.v2 dataset is a set of noisy colour iris images designed to simulate visible wavelength iris acquisition at-a-distance and on-the-move. This paper presents an examination of some of the characteristics that can impact the performance of iris recognition in the UBIRIS.v2 dataset. This dataset consists of iris images in the visible wavelength and was designed to be noisy. The quality and characteristics of these images are surveyed by examining seven different channels of information extracted from them: red, green, blue, intensity, value, lightness, and luminance. We present new quality metrics to assess the image characteristics with regard to focus, entropy, reflections, pupil constriction and pupillary boundary contrast. The results clearly suggest the existence of different characteristics for these channels and could be exploited for use in the design and evaluation of iris recognition systems.

Item Type: Article
Uncontrolled keywords: UBIRIS v2 dataset, iris recognition, iris recognition systems
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics (see also: telecommunications) > TK7880 Applications of electronics (inc industrial & domestic) > TK7882.B56 Biometrics
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: J. Harries
Date Deposited: 04 Nov 2011 11:49
Last Modified: 23 May 2014 09:22
Resource URI: (The current URI for this page, for reference purposes)
  • Depositors only (login required):