Iris (anatomy)

About: Iris (anatomy) is a research topic. Over the lifetime, 5807 publications have been published within this topic receiving 75107 citations.

A human identification technique using images of the iris and wavelet transform

Abstract: A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.

Recognition of Human Iris Patterns for Biometric Identification

Abstract: A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. However, published results have usually been produced under favourable conditions, and there have been no independent trials of the technology. The work presented in this thesis involved developing an ‘open-source’ iris recognition system in order to verify both the uniqueness of the human iris and also its performance as a biometric. For determining the recognition performance of the system two databases of digitised greyscale eye images were used. The iris recognition system consists of an automatic segmentation system that is based on the Hough transform, and is able to localise the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region was then normalised into a rectangular block with constant dimensions to account for imaging inconsistencies. Finally, the phase data from 1D Log-Gabor filters was extracted and quantised to four levels to encode the unique pattern of the iris into a bit-wise biometric template. The Hamming distance was employed for classification of iris templates, and two templates were found to match if a test of statistical independence was failed. The system performed with perfect recognition on a set of 75 eye images; however, tests on another set of 624 images resulted in false accept and false reject rates of 0.005% and 0.238% respectively. Therefore, iris recognition is shown to be a reliable and accurate biometric technology.

Iris recognition system.

Abstract: Methods and apparatus for identifying an eye, especially a human eye (10), on the basis of the visible features of the iris (20) and pupil (30). The eye is first illuminated until the pupil reaches a predetermined size, at which an image of the iris and pupil is obtained. This image is then compared with stored image information for identification. The stored image information is previously obtained from an eye, the pupil of which was similarly brought to the same predetermined size. The illumination of the iris may include oblique illumination from several positions around the circumference of the iris. The illumination from each position may be relatively monochromatic, so that the resulting shadow will lack the color of the light source (172) at that position providing better contrast for elevation-dependent features. A system for performing iris recognition (100) may include a processor (190) which controls an illumination control circuit (170) and a camera (180) to obtain images at several predetermined sizes of the pupil.

Wolff's Anatomy of the Eye and Orbit

Abstract: Bony orbit and paranasal sinuses Ocular appendages Orbital and cerebral vessels Extraocular muscles and ocular movements Innervation and nerves of the orbit The eyeball and its dimensions Cornea and sclera Anterior chamber and drainage angle The iris Posterior chamber and ciliary body Choroid and uveal vessels Lens and zonules The vitreous The retina Visual pathway Autonomic aminergic, peptidergic and nitrergic innervation of the eye Development of the human eye References and further reading.

Automated, non-invasive iris recognition system and method

Abstract: Iris recognition is achieved by iris acquisition that permits a user to self-position his or her eye (216) into an imager's (200) field of view without the need for any physical contact, spatially locating the data defining that portion of a digitized video image of the user's eye that defines solely the iris thereof without any initial spatial condition of the iris being provided, and pattern matching the spatially located data defining the iris of the user's eye with stored data defining a model iris by employing normalized spatial correlation for first comparing, at each of a plurality of spatial scales, each of distinctive spatial characteristics of the respective irises that are spatially registered with one another to quantitatively determine, at each of the plurality of spatial scales, a goodness value of match at that spatial scale, and then judging whether or not the pattern which manifests solely the iris of the user's eye matches the digital data which manifests solely the model iris in accordance with a certain combination of the quantitatively-determined goodness values of match at each of said plurality of spatial scales.