Foolproof iris recognition technology?

Iris recognition is seen as the most accurate biometric recognition technology because no two irises are identical. And researchers at the University of Bath in England have developed new computer algorithms which are 100 per cent accurate in initial trials.

For almost twenty years, the iris recognition research field has been hampered because of a broad patent covering it. As this patent recently expired, many teams around the world are again working on new technologies in this field. Iris recognition is in fact seen as the most accurate biometric recognition technology because no two irises are identical. And researchers at the University of Bath in England have developed new computer algorithms which are 100 per cent accurate in initial trials. Now the researchers are putting online a database of 16,000 iris images collected mainly from students. The source code is also available if you want to further improve the algorithms.

Before going further, let's go back in time to understand why this research field was almost inactive for twenty years. Life Style Extra tells us the story.

Looking into a camera to confirm your identity would now be routine and - were it not for the US firm's virtual monopoly of the technology - it would already be in use at cashpoints and passport control. Its backers say it could reduce fraud and illegal immigration.
Iridian Technologies, based in New Jersey, patented the system of identifying people using the coloured part of the human eye in the mid 80s and other scientists have had to pay tens of thousands of American dollars to do any research in the field, thus hampering competition.
But the patent expired in the US earlier this year and expires in the rest of the world in February 2006.

Now, it's time to return to 2005 at the University of Bath.

Engineers are currently road-testing their technology using a specially-constructed database containing thousands of iris images collected from students and colleagues at the University.
By making this database available to other research groups, the researchers hope to encourage more advances in iris recognition and overcome some of the restrictions caused by a generic patent (recently expired) which has limited innovation for the last two decades.
"Our new algorithm does the same job as the one used by almost all of the commercially available iris recognition systems, it just does it better," said Professor Don Monro from the University’s Department of Electronic and Electrical Engineering.

Below is a picture showing how an iris picture is shot and rendered on a computer screen before being analyzed (Credit: Smart Sensors Ltd.).

The iris image acquisition process

And below is an illustration of the iris image normalization process (Credit: Smart Sensors Ltd.).

The iris image normalization process

First, the inner and outer iris boundaries are located to eliminate the pupil, eyelid and other "clutter". Then the iris image is transformed from polar coordinates to a 512x80 fixed size rectangular image to reduce the effect of iris dilation and contraction, of which 512x48 will be coded. The non-uniform background illumination is finally homogenized.

Now that you know how this new technology works, why are these researchers willing to share their database? Here are Monro's answers.

Most of the databases that are available are held by commercial interests, so it is difficult for independent researchers to make headway in this field.
We are making the database available online so that researchers around the world can use it to develop their own products. So far, more than 30 research groups have applied to use it.

If you want to know more about this project, here are two links at the University of Bath about the Iris Image Database and the Iris Capture Project.

And for even more information, one of the industrial partners of the University of Bath for this project is a U.K. company named Smart Sensors Ltd., which has published two interesting papers about this iris recognition technology.

Here are the links to these documents, "Novel high performance iris feature extraction techniques" (PDF format, 1 page, 119 KB) and "Complexity low complexity human iris feature coding human iris feature coding" (PDF format, 1 page, 222 KB). The above illustrations were extracted from these documents.

Sources: University of Bath news release, November 15, 2005; Life Style Extra, November 15, 2005; and various web sites

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