Now, knee scans can help identify people

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Press Trust of India Washington
Last Updated : Jan 29 2013 | 2:34 PM IST

Just as a fingerprints and other body parts are unique to us as individuals and so can be used to prove who we are, so too are our kneecaps.

Computer scientist Lior Shamir of Lawrence Technological University in Southfield, Michigan, has now demonstrated how a knee scan could be used to single us out.

The approach based on Magnetic resonance imaging (MRI) could be used to quickly register and identify people in a moving queue as they approach passport control at airports for instance or as they walk through the entrance to an office block or other building.

Shamir has tested the approach and achieved accuracy of around 93 per cent, this coupled with other factors such as possession of the correct passport, being in the right place at the right time or tied to other biometrics such as iris recognition and signature analysis could be used to prevent deception and fraud.

Contact lenses can be used to dupe iris recognition systems, passports can be forged.

"Deceptive manipulation requires an invasive and complicated medical procedure, and therefore it is more resistant to spoofing compared to methods such as face, fingerprints, or iris," Shamir said in a statement.

It would be almost impossible to fake one's internal body parts including the kneecaps. Of course, kneecaps are a renowned target of irreversible and deleterious adjustment in the criminal world, but even then shattered kneecaps are likely to be unique to the victim in any case.

MRI scanning avoids health risk of scanning with ionising radiation, such as X-rays, it would also avoid some of the privacy issues that have arisen with terahertz scanners that can "see" beneath a person's clothing, whereas MRI goes more than skin deep.

"Further studies will develop the concept of internal biometrics, and will lead to automatic identification methods that are highly resistant to spoofing," concluded Shamir.

  

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First Published: Jan 24 2013 | 5:35 PM IST

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