![]() This is not a small issue given the fact that cataracts are one of the most common eye diseases. Consequently, any opacification of the lens, called cataract formation, has the potential to alter the retinal scan, but a cataract will never affect an iris scan. The lens of the eye is anatomically behind the iris but is in front of the retina. On the other hand, the iris image is largely unaffected by the corneal refractive state.īoth retinal and iris images, however, will be altered dramatically by anything that results in a loss of corneal clarity, such as corneal scarring, corneal edema, and some cosmetic contact lenses. Consequently, unless a highly myopic, hyperopic, or astigmatic individual is wearing contact lenses, that individual will have a defocused retinal image when they take off their glasses for scanning. Common corneal diseases that do not cause loss of tissue clarity, but do result in corneal “warping” (e.g., keratoconus), may also adversely affect retinal scanning accuracy. Common refractive disorders that could alter retinal scanning include high degrees of near-sightedness (myopia), far-sightedness (hyperopia), and astigmatism. In contrast to retinal scanning, iris scanning is largely unaffected by the optical or refractive state of the eye. John Daugman, by virtue of his iris scan algorithms, is extremely important in the development of this powerful tool. At this point in time the iris scan is an extremely appealing biometric identifier. It has also been demonstrated a 2 GHz processer can compare a particular iris scan with the scans of 1 million others in less than 2 seconds. Furthermore, it appears that any given iris scan is stable over many years. Even the same individual’s two eyes and the eyes of genetically identical twins, all have distinctly different irises. ![]() One of these is the uniqueness of each iris. Of all the biometric identifiers that have been utilized, iris scans offer many advantages. This concept has to do with the degree of certainty of absolute iris identification depending upon the degree of idealness of the camera, distance from the iris, and quality of illumination at the time the scan is done. He also discusses the decidability index. The uniqueness of failing the test of statistical independence forms the basis of iris recognition. He includes algorithms to also allow for differences in pupil size and orientation of the eye. Daugman has improved upon his original algorithms to include ways of now taking into account confounding artifacts from eyelids, eyelashes, or hard contact lens edges. Altogether 2048 phase bits are calculated for each iris. Iris feature detail is demodulated for its phase information using 2-D Gabor wavelets. Near-infrared wavelengths of light are used for the purpose of iris scanning. This particular landmark paper explains these algorithms and presents results of over 9 million comparison iris images from four countries. He is responsible for developing the complex iris recognition algorithms (mathematical formulae) that enable the use of this technique. Daugman has pioneered much of the work in this area. Of all the possible biometric identifiers iris scans are the most reliable.ĭr. ![]() More recently there has been interest in biometric identifiers that can through physical characteristics be utilized to assist in this process. User names, passwords, and tokens are all examples of what can and has been used for these purposes. In recent years there has been increasing interest in the ability to absolutely authenticate and/or identify individuals. The reason one can easily see another person’s iris with the naked eye, but cannot visualize another person’s retina, is largely due to the complexity of the optics needed to visualize the retina compared to the iris.ĭaugman, John G., PhD, How Iris Recognition Works, IEEE Transactions on Circuits and Systems for Video Technology, Vol.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |