Iris recognition
Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance.
[3] Retinal scanning is a different, ocular-based biometric technology that uses the unique patterns on a person's retina blood vessels and is often confused with iris recognition.
Although John Daugman developed and in the 1990s patented the first actual algorithms to perform iris recognition, published the first papers about it and gave the first live demonstrations, the concept behind this invention has a much longer history and today it benefits from many other active scientific contributors.
")[citation needed] The core theoretical idea in Daugman's algorithms is that the failure of a test of statistical independence can be a very strong basis for pattern recognition, if there is sufficiently high entropy (enough degrees-of-freedom of random variation) among samples from different classes.
In 1994 he patented this basis for iris recognition and its underlying computer vision algorithms for image processing, feature extraction, and matching, and published them in a paper.
In the United Arab Emirates, all 32 air, land, and seaports deploy these algorithms to screen all persons entering the UAE requiring a visa.
Because a large watch-list compiled among GCC States is exhaustively searched each time, the number of iris cross-comparisons climbed to 62 trillion in 10 years.
[5] In a different type of application, iris is one of three biometric identification technologies internationally standardised since 2006 by ICAO for use in e-passports (the other two are fingerprint and face recognition).
[17] Iris melanin, also known as chromophore, mainly consists of two distinct heterogeneous macromolecules, called eumelanin (brown–black) and pheomelanin (yellow–reddish),[18][19] whose absorbance at longer wavelengths in the NIR spectrum is negligible.
If the Hamming distance is below the decision threshold, a positive identification has effectively been made because of the statistical extreme improbability that two different persons could agree by chance ("collide") in so many bits, given the high entropy of iris templates.
The iris of the eye has been described as the ideal part of the human body for biometric identification for several reasons: It is an internal organ that is well protected against damage and wear by a highly transparent and sensitive membrane (the cornea).
If a human can verify the process by which the iris images are obtained (at a customs station, entering or even walking by an embassy, as a desktop 2nd factor for authentication, etc.)
or through the use of live eye detection (which varies lighting to trigger slight dilation of the pupil and variations across a quick scan which may take several image snapshots) then the integrity of the identification are extremely high.
The reliability of any biometric identification depends on ensuring that the signal acquired and compared has actually been recorded from a live body part of the person to be identified and is not a manufactured template.
[citation needed] Other methods include using spectral analysis instead of merely monochromatic cameras to distinguish iris tissue from other material; observing the characteristic natural movement of an eyeball (measuring nystagmus, tracking eye while text is read, etc.
); testing for retinal retroreflection (red-eye effect) or for reflections from the eye's four optical surfaces (front and back of both cornea and lens) to verify their presence, position and shape.
[31] Another proposed[citation needed] method is to use 3D imaging (e.g., stereo cameras) to verify the position and shape of the iris relative to other eye features.
A 2004 report[citation needed] by the German Federal Office for Information Security noted that none of the iris-recognition systems commercially available at the time implemented any live-tissue verification technology.
