Ears Could Make Better Unique IDs Than Fingerprints

The ear might be the best way to identify people, scientists say.

ByABC News
November 15, 2010, 5:34 PM

Nov. 16, 2010— -- On a planet hosting 6.7 billion human beings, having proof you're unique is of tantamount importance. The ear, it turns out, may be the best identification yet.

Through a new shape-finding algorithm called "image ray transform," which boasts 99.6 percent accuracy, according to a study presented at the IEEE Fourth International Conference on Biometrics Sept. 29, the outer ear may prove to be one of the most accurate and least intrusive ways to identify people.

Fingerprint databases of U.S. government agencies alone store the records of more than 100 million people, but prints can rub off or callous over during hard or repetitive labor. With the advent of computer vision, researchers and identification industries are seeking easier and more robust biometrics to get their hands on.

"When you're born your ear is fully formed. The lobe descends a little, but overall it stays the same. It's a great way to identify people," said Mark Nixon, a computer scientist at the University of Southampton. and leader of the research.

"There's real power in using the appearance of an ear for computer recognition, compared to facial recognition. It's roughly equivalent if not better," said computer scientist Kevin Bowyer of Notre Dame, who is pursuing his own ear-recognition technology and not involved with Nixon's work. "If you've got a profile image for someone, this is a great way to use it."

Recent technologies use computer vision to convert human features, such as faces and irises, even the gait of a person's walk, into reliable alternatives to fingerprints. Nixon and his team have pursued using ears as one biometric for years, and through what he called a "blue-sky research effort," his colleagues created the highly capable image-ray-transform algorithm.

The technology can identify an ear time after time with 99.6 percent accuracy. It works by unleashing a ray-producing algorithm on an image to seek out curved features. When a ray finds one, the software draws over the part and repeats the analysis. In a few hundred or thousand cycles, it cleanly paints the ear more than any other face structure.