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Study advances iris images as a long-term form of identification

Date:
August 20, 2013
Source:
National Institute of Standards and Technology (NIST)
Summary:
A new report by biometric researchers uses data from thousands of frequent travelers enrolled in an iris recognition program to determine that no consistent change occurs in the distinguishing texture of their irises for at least a decade. These findings inform identity program administrators on how often iris images need to be recaptured to maintain accuracy.
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A new report by biometric researchers at the National Institute of Standards and Technology (NIST) uses data from thousands of frequent travelers enrolled in an iris recognition program to determine that no consistent change occurs in the distinguishing texture of their irises for at least a decade. These findings inform identity program administrators on how often iris images need to be recaptured to maintain accuracy.

For decades, researchers seeking biometric identifiers other than fingerprints believed that irises were a strong biometric because their one-of-a-kind texture meets the stability and uniqueness requirements for biometrics. However, recent research has questioned that belief. A study of 217 subjects over a three-year period found that the recognition of the subjects' irises became increasingly difficult, consistent with an aging effect.

To learn more, NIST biometric researchers used several methods to evaluate iris stability.

Researchers first examined anonymous data from millions of transactions from NEXUS, a joint Canadian and American program used by frequent travelers to move quickly across the Canadian border. As part of NEXUS, members' irises are enrolled into the system with an iris camera and their irises are scanned and matched to system files when they travel across the border. NIST researchers also examined a larger, but less well-controlled set of anonymous statistics collected over a six-year period.

In both large-population studies, NIST researchers found no evidence of a widespread aging effect, said Biometric Testing Project Leader Patrick Grother. A NIST computer model estimates that iris recognition of average people will typically be useable for decades after the initial enrollment.

"In our iris aging study we used a mixed effects regression model, for its ability to capture population-wide aging and individual-specific aging, and to estimate the aging rate over decades," said Grother. "We hope these methods will be applicable to other biometric aging studies such as face aging because of their ability to represent variation across individuals who appear in a biometric system irregularly."

NIST researchers then reanalyzed the images from the earlier studies of 217 subjects that evaluated the population-wide aspect. Those studies reported an increase in false rejection rates over time -- that is, the original, enrolled images taken in the first year of the study did not match those taken later. While the rejection numbers were high, the results did not necessarily demonstrate that the iris texture itself was changing. In fact, a study by another research team identified pupil dilation as the primary cause behind the false rejection rates. This prompted the NIST team to consider the issue.

Further information: http://www.nist.gov/manuscript-publication-search.cfm?pub_id=913900


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Materials provided by National Institute of Standards and Technology (NIST). Note: Content may be edited for style and length.


Cite This Page:

National Institute of Standards and Technology (NIST). "Study advances iris images as a long-term form of identification." ScienceDaily. ScienceDaily, 20 August 2013. <www.sciencedaily.com/releases/2013/08/130820161301.htm>.
National Institute of Standards and Technology (NIST). (2013, August 20). Study advances iris images as a long-term form of identification. ScienceDaily. Retrieved March 28, 2024 from www.sciencedaily.com/releases/2013/08/130820161301.htm
National Institute of Standards and Technology (NIST). "Study advances iris images as a long-term form of identification." ScienceDaily. www.sciencedaily.com/releases/2013/08/130820161301.htm (accessed March 28, 2024).

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