Ear-Prints and the Future of Digital Security

Advancing technologies have revealed a prospective yet unexpected biometric that rivals fingerprints in uniqueness and might be just as common as them in the future: ears.

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Identity is crucial in today’s enormously populated world. At Stuyvesant, its importance is demonstrated daily when we scan our student ID cards to enter the school building. Identification has many uses and forms, including passports, social security cards, and fingerprints. Recently, scientists developed a new biometric to identify people more conveniently than the conventional fingerprints and irises: ears.

Biometrics are physical characteristics that are unique to every individual. Our ears are fully formed from the day we’re born and their shapes are unique to every one of us. The lobes––the bottom tips of the ears––elongate a little as humans age, but this is a measurable change. The overall structure of the ear stays the same regardless of age, unlike many other established biometrics. Recognizing this, Mark Nixon, along with computer scientists Alastair Cummings and John Carter, presented a paper at the IEEE Fourth International Conference on Biometrics introducing a successful software to identify individuals using ears with image ray transform technology.

Image ray transform software is a shape-finding algorithm that distinguishes the helix, or outer edge, of our ear. As such, profile pictures are ideal for this technology. First, beams of light are shone into the image of the ear. The light rays bounce off the numerous tubular features in the helix and the software captures the resulting reflections of light. Then, these reflections are analyzed and the software processes them repeatedly until a clear image of the ear appears.

However, during experiments, hair blocking the ear or glasses behind the ear altered the vessel’s orientation, making the images flawed. To solve this, Nixon, Cummings, and Carter modified the algorithm such that the software could distinguish and isolate the ear and the head. This new algorithm proved to be extremely accurate, boasting a 99.6 percent accuracy rate throughout the analyses of over 250 ear images. An additional program has been able to translate the tubular features of the helix into a specific set of numbers, creating “ear IDs.”

Nixon claims that since the software functions correctly under any facial expression and background, it is a dependable identifier. However, critics state that fingerprints, having been used for over 100 years, have proven to be accurate and easy enough to remain the primary biometric. Others remain skeptical about the accuracy of ear biometrics and believe that common biometrics such as fingerprints and irises will remain superior. After all, ear identification still has its flaws. For example, ear shapes can be converted with plastic surgery or piercings. Joseph Santos-Sacchi, a Yale professor of otolaryngology, physiology, and neurobiology, remarked that people can manipulate their ears with jewelry, altering the shapes of their ears and making the biometric less effective.

But fingerprints are not faultless either. Experts say that it is quite common for fingerprints to rub off or for obstructive calluses to develop as a result of hard labor or accidents. Furthermore, Kevin Bowyer, a computer scientist at Notre Dame who is also researching ear-identifying technology, cites degraded biometric performances in irises. Inaccuracies with iris identification are especially prone with older people. According to the CSIR (Council of Scientific and Industrial Research), infants sleep most of the time, so identifying them through irises is challenging. Moreover, while fingerprint patterns remain the same throughout one’s life, the size of the pattern changes in scale as the individual grows, and current fingerprint-related technology cannot account for this.

The goal of the advancing ear-recognition technology is not to replace fingerprints, but to assist them in identification. After all, the more biometrics there are, the more accurate identification will become. Researchers are working on modifying the algorithm further by connecting it with other computer-vision technologies, expanding its applications and improving its speed. This can transform grainy security camera footage of criminals into quality “courtroom-worthy” evidence.

The ability to distinguish structural features highlights the amazing potential of image ray transform technology. Researcher Alastair Cummings proposed an interesting insight on this matter: “The ray transform technique may also be appropriate for use in gait biometrics, as legs act as tubular features that the transform is adept at extracting.” This technology could even progress to identifying people simply by the way they walk.

Overall, ears as biometrics can lead to higher probabilities of solving crimes, catching criminals, and saving lives. Considering the speed at which technology is developing, students may soon be scanning their ears to enter the school instead of swiping IDs.