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Iris recognition biometric systems apply mathematical pattern-recognition techniques to images of the irises of an individual's eyes.. 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 ...
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Daugman filed for a patent for his iris recognition algorithm [1] in 1991 while working at the University of Cambridge. [9] The algorithm was first commercialized in the late 1990s. His algorithm automatically recognizes persons in real-time by encoding the random patterns visible in the iris of the eye from some distance, and applying a ...
Besides fingerprint and facial recognition, eye scanning is one of the most highly mentioned biometric modalities these days. As the security market rapidly increases, it is expected that eye ...
Iris recognition is widely applied by organisations dealing with the masses, one being the Aadhaar identification carried out by the Government of India to keep records of its population. The reason for this is that iris recognition makes use of iris prints of humans, which hardly evolve during one's lifetime and are extremely stable.
Capturing data can be done in various ways; the best method depends on application. In biometric security systems, capture is the acquisition of or the process of acquiring and identifying characteristics such as finger image, palm image, facial image, iris print, or voiceprint which involves audio data, and the rest all involve video data.
The elasticity of the iris subjects the shape and degree of circularity of the pupil to variations. For example, the pupil's border may slightly wobble and alter in shape within the iris during changes in pupil size [7] and eye-movements, [6] which can be problematic for eye trackers which base their gaze estimation on the center mass of the pupil border.
This comparison of optical character recognition software includes: OCR engines, that do the actual character identification; Layout analysis software, that divide scanned documents into zones suitable for OCR; Graphical interfaces to one or more OCR engines