Top: Sample iris image acquired with LG 4000 iris sensor in March 2008. Bottom: Sample image of same iris acquired with LG 4000 iris sensor in March 2011.

Since
the early days of iris recognition technologies, it has been assumed
that the iris was a “stable” biometric over a person’s lifetime—”one
enrollment for life.” However, new research from University of Notre
Dame researchers has found that iris biometric enrollment is susceptible
to an aging process that causes recognition performance to degrade
slowly over time.

   

“The
biometric community has long accepted that there is no ‘template aging
effect’ for iris recognition, meaning that once you are enrolled in an
iris recognition system, your chances of experiencing a false non-match
error remain constant over time,” Kevin Bowyer, Notre Dame’s
Schubmel-Prein Family Chair in Computer Science and Engineering, said.
“This was sometimes expressed as ‘a single enrollment for life.’ Our
experimental results show that, in fact, the false non-match rate
increases over time, which means that the single enrollment for life
idea is wrong.

   

“The
false match rate is how often the system says that two images are a
match when in truth they are from different persons. The false non-match
rate is how often the system says that two images are not a match when
in truth they are from the same person.”

   

Bowyer noted that there are several reasons the misconceptions about iris biometric stability has persisted.

   

“One
reason is that because it was believed from the early days of iris
recognition that there was no template aging effect, nobody bothered to
look for the effect,” he said. “Also, only recently have research groups
had access to image datasets acquired for the same people over a period
of several years. Recently, another biometric research group (from
Clarkson University and West Virginia University) has also published a
study that finds an iris template aging effect.”

   

In
their study, Bowyer and Notre Dame undergraduate Sam Fenker analyzed a
large dataset with more images acquired over a longer period of time.
For one group of people in their dataset, they were able to analyze a
year-to-year change over three successive years.

   

Bowyer
points out that iris recognition is already used in various airports
and border crossings, including London airports, Schiphol 9Amsterdam)
airport, and border entry in the United Arab Emirates. And probably the
highest profile and largest application of iris biometrics currently
underway is the Unique ID program in India, which has enrolled more
people that live in the United Kingdom.

   

Despite the results of the study, Bowyer does not see them as a “negative” for iris recognition technologies.

   

“I
do not see this as a major problem for security systems going forward,”
he said. “Once you have admitted that there is a template effect and
have set up your system to handle it appropriately in some way, it is no
longer a big deal. One possibility is setting up a reenrollment
interval. Another possibility is some type of ‘rolling re-enrollment,’
in which a person is automatically re-enrolled each time they are
recognized. And, in the long run, researchers may develop new approaches
that are ‘aging-resistant.’ The iris template aging effect will only be
a problem for those who for some reason refuse to believe that it
exists.”

   

Bowyer and Fenker recently presented their research paper at the IEEE Computer Society Biometrics Workshop.

   

A copy of the paper is available at: http://www.cse.nd.edu/~kwb/FenkerBowyerCVPRW_2012.pdf

Source: University of Notre Dame