Part based bit error analysis of iris codes

Tomeo-Reyes, Inmaculada & Chandran, Vinod (2016) Part based bit error analysis of iris codes. Pattern Recognition, 60, pp. 306-317.

[img] PDF (2MB)
Administrators only until December 2018 | Request a copy from author
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

View at publisher


In order to effectively use iris patterns in biometric recognition, there is value in knowing how bit errors in iris codes are distributed. In this work, the iris is considered in a part-based framework as rings and sectors. A mean normalised bit error is defined as the bit error averaged over the entire part and over an ensemble of images. The distribution of this error for genuine comparisons is investigated as a function of radius (ring) and angle (sector) for a range of factors more comprehensively than previous studies of consistency of iris codes. Two iris recognition systems and three data sets are used. The effect of residual segmentation errors after automated segmentation is checked, and masks are manually refined to obtain segmentation error free data for further investigation. The effect of factors such as capture sensor, resampling, input iris image resolution, filter type and encoding scheme, and changes in pupil size is systematically investigated. Results confirm the finding in previous works that the pupillary and limbic boundaries are more error-prone than the middle region of the iris. This study further confirms that this V-shaped radial trend is not significantly disturbed by any of the above factors other than pupil size changes. Both pupil dilation and constriction result in increased bit errors which no longer show a dip in the middle region of the iris. The distribution of errors as a function of angle is approximately uniform regardless of the factor investigated but shows a small decrease towards the sectors near the eye corners.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 98251
Item Type: Journal Article
Refereed: Yes
Keywords: Iris recognition, Iris code, Consistent bits, Error distribution
DOI: 10.1016/j.patcog.2016.05.022
ISSN: 0031-3203
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 Elsevier Ltd.
Deposited On: 18 Aug 2016 23:04
Last Modified: 23 Aug 2016 17:54

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page