Paper
12 May 2016 Comparison and evaluation of datasets for off-angle iris recognition
Osman M. Kurtuncu, Gamze N. Cerme, Mahmut Karakaya
Author Affiliations +
Abstract
In this paper, we investigated the publicly available iris recognition datasets and their data capture procedures in order to determine if they are suitable for the stand-off iris recognition research. Majority of the iris recognition datasets include only frontal iris images. Even if a few datasets include off-angle iris images, the frontal and off-angle iris images are not captured at the same time. The comparison of the frontal and off-angle iris images shows not only differences in the gaze angle but also change in pupil dilation and accommodation as well. In order to isolate the effect of the gaze angle from other challenging issues including dilation and accommodation, the frontal and off-angle iris images are supposed to be captured at the same time by using two different cameras. Therefore, we developed an iris image acquisition platform by using two cameras in this work where one camera captures frontal iris image and the other one captures iris images from off-angle. Based on the comparison of Hamming distance between frontal and off-angle iris images captured with the two-camera- setup and one-camera-setup, we observed that Hamming distance in two-camera-setup is less than one-camera-setup ranging from 0.05 to 0.001. These results show that in order to have accurate results in the off-angle iris recognition research, two-camera-setup is necessary in order to distinguish the challenging issues from each other.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Osman M. Kurtuncu, Gamze N. Cerme, and Mahmut Karakaya "Comparison and evaluation of datasets for off-angle iris recognition", Proc. SPIE 9825, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defense, and Law Enforcement Applications XV, 98250O (12 May 2016); https://doi.org/10.1117/12.2222759
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Cited by 1 scholarly publication.
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KEYWORDS
Iris recognition

Cameras

Iris

Databases

Eye

Image acquisition

Refraction

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