Iris recognition is a method of biometric authentication that uses pattern-recognition techniques based on high-resolution images of the irides of an individual's eyes.Not to be confused with another, less prevalent, ocular-based technology, retina scanning, iris recognition uses camera technology, with subtle infrared illumination reducing specular reflection from the convex cornea, to create images of the detail-rich, intricate structures of the iris. Converted into digital templates, these images provide mathematical representations of the iris that yield unambiguous positive identification of an individual.
Iris recognition efficacy is rarely impeded by glasses or contact lenses. Iris technology has the smallest outlier (those who cannot use/enroll) group of all biometric technologies. Because of its speed of comparison, iris recognition is the only biometric technology well-suited for one-to-many identification. A key advantage of iris recognition is its stability, or template longevity, as, barring trauma, a single enrollment can last a lifetime.
Breakthrough work to create the iris-recognition algorithms required for image acquisition and one-to-many matching was pioneered by John G. Daugman, Ph.D, OBE (University of Cambridge Computer Laboratory). These were utilized to effectively debut commercialization of the technology in conjunction with an early version of the IrisAccess system designed and manufactured by Korea's LG Electronics. Daugman's algorithms are the basis of almost all currently (as of 2006) commercially deployed iris-recognition systems. (In tests where the matching thresholds are—for better comparability—changed from their default settings to allow a false-accept rate in the region of 10−3 to 10−4, the IrisCode false-reject rates are comparable to the most accurate single-finger fingerprint matchers.
The majority of iris recognition benchmarks are implemented in Near Infrared (NIR) imaging by emitting 750nm wavelength light source. This is done to avoid light reflections from cornea in iris which makes the captured images very noisy. Such images are challenging for feature extraction procedures and consequently hard to recognize at the identification step. Although, NIR imaging provides good quality images, it loses pigment melanin information, which is a rich source of information for iris recognition...............
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