How Iris Recognition Compares to Other Biometrics
Few would argue with the generally held view - and evidence
- that iris recognition is the most accurate of the commonly
used biometric technologies. There are a number of other
factors that weigh heavily in iris recognition's favor
for applications requiring large databases and real-time
||Like a snowflake, every iris is absolutely
unique. A subject's left and right iris is as different
from each other as they are from any other individual's.
It has been calculated that the chance of finding
two randomly formed identical irises is on an almost
astronomical order of 1 in 1078.
||Another differentiator impacting accuracy is that
no human intervention is required to "set"
thresholds for False Accept and False Reject performance.
Instead, the human element plays no role in performance
standards for this technology, while an unmatched
FAR (false accept rate) performance of 1 in 1.2 million
is delivered. Other electronic authentication technologies
sometimes select a number of templates that represent
"possible matches" - perpetuating the
potential for error, in that final determination
of identity relies on a human interpretation.
||At the root of iris recognition's accuracy is
the data-richness of the iris itself. The IrisAccess
system captures over 240 degrees of freedom or unique
characteristics in formulating its algorithmic template.
Fingerprints, facial recognition and hand geometry
have far less detailed input in template construction.
In fact, it's probably fair to say that one iris
template contains more data than is collected in
creating templates for a finger, a face and a hand
combined. This is one reason why iris recognition
can authenticate with confidence even when significantly
less than the whole eye is visible.
||Virtually every other biometric template
changes significantly over time, detracting from
overall system performance and requiring frequent
reenrollment. Voices change. Hands and fingers grow.
The type of labor one does, even weather temperature
or one's medical condition can result in template
changes in other technologies. Barring trauma and
certain ophthalmologic surgery, the patterns in
the iris are constant from age 1 to death. (At death,
iris tissue is among the most rapidly deteriorating
of all body tissues, something that leads to its
use by forensic pathologists in estimating time
||No other biometric technology is designed
to deliver 1-n searching of large databases in real
time. A 2001 study conducted by the UK's National
Physical Laboratory found iris technology was capable
of nearly 20 times more matches per minute than
its closest competitor. Looking at speed in conjunction
with accuracy, there's simply no other technology
that can deliver high accuracy authentication in
anything close to the real-time performance of iris
||Conversely, fingerprint searches are challenged
by database size, adding time to searches or necessitating
filtering as a search acceleration technique. Even
so, fingerprint technology often returns multiple
"possible matches," forcing introduction
of human decision factors and increasing the potential
for error in an authentication decision.
||Iris Recognition and the LG IrisAccess
3000 are ideal for large-scale ID applications or
enterprise physical security and applications characterized
by large databases. As iris data templates require
only 512-bytes of storage per iris, very large databases
can be managed and speedily searched without degradation
of performance accuracy.
||No bright lights or lasers are used
in the imaging and iris authentication process.
The user can stand as far as 10" away from
the unit, and even wear glasses or contact lenses
without compromising system accuracy. Unlike some
other popular biometrics, iris authentication involves
no physical contact. Not only does this mean "no
touch" authentication, it also means the technology
is ideally suited for use in environments where
rubber gloves or other protective gear is used.
||Iris recognition applications are generally opt-in
- there is none of the surveillance stigma sometimes
affiliated with facial recognition, which scans
crowds looking for individuals. Nor is there any
tie-in to the large fingerprint databases maintained
by law enforcement agencies, which often gives a
negative stigma to fingerprint-based systems.