Thoughtful Biometrics for Iris — Part 4
This article is the fourth in an introductory series leading up to the Thoughtful Biometrics Workshop 8,10,12 March 2021.
A few years ago, Samsung pioneered the concept of leveraging iris recognition as an added layer of security, beyond numerical passwords — or even fingerprints. To most people, this concept seemed possible only in futuristic sci-fi tales or for spy thrillers before Samsung’s announcement. For those unfamiliar with iris recognition technology or wondering “why would I ever want to use this,” here is a brief primer:
Is it Ocular or Iris recognition?
The term ocular, derived from its Latin root oculus, broadly refers to the anatomical regions and structures related to the eye. Ocular biometrics refers to the recognition (identification or verification) of individuals using the information offered by ocular modalities. The public perception of ocular biometrics has been largely limited to iris recognition. However, research suggests that several other ocular modalities could serve as biometric indicators, such as retina (retinal vascular pattern inside the eye globe), conjunctival vasculature (the blood vessel patterns observed in the sclera, or white, of the eye), and the ocular region of the face (the eye and the areas around it, including the iris, conjunctiva (white of the eye), eyelashes and the eyelids (if the eye is closed), eyebrows, and moles/scars around the eye).
Of all the ocular biometric traits, however, the iris is considered to be the most reliable. This is based on its uniqueness, performance, and circumvention properties.
Iris as a Biometric
As you may recall from Biology 101, the iris (plural: irides) is a thin, colored circular structure in the eye, located just behind the cornea and in front of the lens. It is responsible for controlling the diameter and size of the pupil, as well as the amount of light reaching the retina.
The iris is the only internal organ readily visible from the outside. Unlike facial expressions, aging doesn’t usually alter its pattern because it is not exposed to the elements. People’s faces take on a weathered appearance as they age precisely because they are affected by the sun, wind, dirt, and other factors.
Irises exhibit an extraordinary amount of textural details that are believed to be different between individuals and between different eyes of the same individual. The texture of an iris can be described as a multilayered, tangled mesh-like structure that imparts a highly complex texture to its surface. Compared with fingerprints, iris image data acquisition is usually non-invasive. Thus, the iris has become one of the most reliable biometric traits for identity verification and recognition.
What type of technology is needed to successfully capture an iris biometric?
Capturing the texture of irises using a traditional camera is challenging. Iris images are typically acquired using sensors that operate in the near-infrared (NIR) spectrum. The wavelength of the illuminating sources ranges between 700–900nm. The usage of the NIR spectrum for iris recognition provides two critical benefits. First, it is observed that the effect of melanin, a color-inducing compound, is negligible at longer wavelengths. Using the NIR spectrum ensures that the acquired image reveals information related to the iris' texture rather than its pigmentation. Second, compared to the visible spectrum, the texture of dark-colored irides can be well observed using NIR.
Iris Representation and Matching
Patterns of the left iris of an individual are assumed to be different from those of the right iris in the context of iris recognition systems. Therefore, during the enrollment phase of an iris-based authentication system, the operator/user must indicate the iris from which eye is enrolled. Then, during recognition, the system must capture the iris from the same eye image so that it can be successfully matched with the corresponding one in the database. Most of the iris-based authentication systems analyze the iris texture for recognition.
The iris' texture is formed by many interlacing minute characteristics, such as pigment spots, stripes, furrows, and crypts, that are embedded on a stroma. Based on these features, the recognition takes place. But, prior to recognition, the iris region must first be localized and segmented from an image of the eye. Errors in the segmentation step will lead to poor performance due to the inclusion of noise (eyelashes, sclera, pupil, eyelids, and specular reflection) in the image.
Several iris representation techniques have been proposed in the literature, and the matching is mainly based on the method of representation — the method used for encoding the iris texture. Thus, most existing techniques for iris recognition can be divided into two major classes. The first class represents the iris texture using filters or transforms, the second class of methods seeks to capture local and macro iris features, such as freckles, crypts, and furrows, in the spatial domain.
Daugman’s phase encoding technique, which falls under the first class, is the most common and promising among the different iris recognition techniques.
First, a camera acquires an image of an eye, and the iris annular region is segmented. Next, the annular iris is geometrically normalized — unwrapped from raw image coordinates to polar coordinates. A texture filter is applied to the normalized iris image, and the filter responses are quantized into a binary representation (iris code). Finally, the comparison between two iris codes is done by computing the fractional HD as a dissimilarity measure.
Should I be worried about any health or privacy issues associated with iris scanning?
Health issues, No!!
The NIR light spectrum isn’t seen by the eyes and doesn’t have any known side effects.
Privacy issues, Maybe!!
Perhaps the biggest threat of iris scanning is the danger of a national database that can track people covertly, at a distance, or in motion, without their knowledge or consent. This raises significant civil liberties and privacy concerns, increasing as iris data, the most accurate image-based biometric modality, is collected from more and more people. It may be possible for law enforcement officers to use long-range iris scanners on people simply glancing in their rearview mirror after being pulled over. At some point, it’s possible that every person could be identified at any place, even if they are not suspected of committing a crime.
There also are grave concerns with local law enforcement sharing biometric data to help federal immigration agencies such as the U.S. Immigration and Customs Enforcement (ICE), which has direct access to many law enforcement databases.
This article is the fourth in an introductory series leading up to the Thoughtful Biometrics Workshop 8,10,12 March 2021. Additional articles can be found as follows:
- A gentle introduction to Thoughtful Biometrics — Part 1
- Thoughtful Biometrics for Facial Recognition — Part 2
- Thoughtful Biometrics for Fingerprints — Part 3
- Thoughtful Biometrics for Iris — Part 4 (this article)
- Thoughtful Biometrics for Voice — Part 5
- Thoughtful Biometrics for DNA — Part 6
- Thoughtful Biometrics Overview — Part 7
- What is Identity Management — Part 8
