The ear is one of the few parts of the body that remains relatively unchanged over our lifetime, making it a useful alternative to facial or fingerprint authentication technologies. This part of the body is unique to each person in the same way as a fingerprints. According to the researchers, even among identical twins, the shape of the ear is unique enough to still serve as a protection. An additional benefit is that, apart from the earlobe falling over time, the inside of the earlobe does not age as much over the years as our face.

The ear recognition software works similarly to face recognition. When a person gets a new phone, they have to register their fingerprint or face for the phone to recognize them. New devices often require users to place their fingers repeatedly over the sensor to get a full “picture” of their fingerprint. And face-recognition technology relies on users moving their faces in certain ways in front of their camera for the device to effectively capture their facial features. The ear recognition algorithm will work the same way.

While setting up a biometric device, the algorithm takes multiple samples of a person’s identity, such as facial images or fingerprints, and logs them into the device. When you go to unlock your device using a biometric, it takes a live sample to compare it to the logs on the device, such as a picture of your face or in this case, a picture of your ear.

Bourlai’s software uses an ear recognition algorithm to evaluate ear scans and determine if they are suitable for automated matching. He employed a variety of ear datasets with a wide range of ear poses to test the software.

The software that Professor Thirimachos Bourlai and his team are working on, has been tested on two large sets of ear images with accuracy of up to 97.25% of the time.

Ear recognition software could be used to enhance existing security systems, such as those used at airports around the world, and camera-based security systems, Bourlai said. His team also plans to enhance their proposed ear recognition algorithm to work well with thermal images as well to account for darker environments where it might be difficult to capture clear visible band images using conventional cameras.

You can read more about Ear Authentication Technology here.

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