Open AccessDilation‐aware enrolment for iris recognition
Author(s) -
Ortiz Estefan,
Bowyer Kevin W.,
Flynn Patrick J.
Publication year - 2016
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
ISSN - 2047-4946
DOI - 10.1049/iet-bmt.2015.0005
Subject(s) - dilation (metric space) , pupillary response , computer science , artificial intelligence , computer vision , iris recognition , pattern recognition (psychology) , mathematics , pupil , biometrics , psychology , combinatorics , neuroscience
Iris recognition systems typically enrol a person based on a single ‘best’ eye image. Research has shown that the probability of a false non‐match result increases with increased difference in pupil dilation between the enrolment image and the probe image. Therefore, dilation‐aware methods of enrolment should improve the accuracy of iris recognition. The authors examine a strategy to improve accuracy through a dilation‐aware enrolment step that selects one or more enrolment images based on the observed distribution of dilation ratios for that eye. Additionally, they demonstrate that an image with median dilation is the optimal single eye image dilation‐aware enrolment choice. Their results confirm that this dilation‐aware enrolment strategy does improve matching accuracy compared with traditional single‐image enrolment, and also compared with multi‐image enrolment that does not take dilation into account.