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IRIS RECOGNITION
Introduction:
Iris recognition combines computer vision, pattern recognition, statistics, and the human-machine interface. The purpose is real-time, high confidence recognition of a person's  identity by mathematical analysis of the random patterns that are visible within the iris of an eye from some distance. Because the iris is a protected internal organ whose random texture is stable throughout life, it can serve as a kind of living passport or a living password that one need not remember but one always carries along. Because the randomness of iris patterns has very high dimensions, recognition decisions are made with confidence levels high enough to support rapid and reliable exhaustive searches through national-sized databases.
The major applications so far have been aviation security, automatic border crossing controls, database access, computer Log-In, building entry, ATMs, and Government programs. In addition to other uses in financial transactions, this technology is forecast to play a role in a wide range of applications in which a person's identity must be established or confirmed. These include electronic commerce, information security, entitlements authorization, building entry, automobile ignition, forensic and police applications, computer Log-In, or any other transaction in which personal identification currently relies just on special possessions or secrets (keys, cards, documents, passwords, PINs).
Enabling Technology:
 The iris is the eye's, which surrounds the pupil. An iris scanner takes a highly detailed of the iris, which is then analyzed. The complex pattern of the iris can contain many distinctive features such as arching ligaments, furrows, ridges, crypts, rings, corona, freckles, and a zigzag collarette. The iris color is determined mainly by the density of melanin pigment in its anterior layer and stroma, with blue irises resulting from an absence of pigment: long wavelength light penetrates and is absorbed by the pigment epithelium, while shorter wavelengths are reflected and scattered by the stroma. To capture the rich details of iris patterns, an imaging system resolves a minimum of 70 pixels in iris radius. Each isolated iris pattern is then demodulated to  extract its phase information using quadrature 2D Gabor wavelets.
Algorithms of Daugman for encoding and recognizing iris patterns have been the executable software used in all iris recognition systems so far deployed commercially or in public trials.
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