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ABSTRACT
This paper deals with the basics of iris, its properties and how it adds some advantageous features to recognize the correct person. In this paper we discuss the details regarding the information about how the iris is located, to distinguish it from other parts of the eye, how the scanner scans the whole pattern of the iris while enrolling and matching and how the scanned patterns are converted into 256 bytes of data so that it can be stored in the database. We compare the iris codes of the current person who wants to access the database and gives the matched results to the user accordingly.
As the iris recognition technology produces very low false rate when compared to the other biometrics results it is very preferable in many systems such as airports ,banks ,defence , etc.., where the security plays one of the major role. But in the case of fields where the database is huge, the comparison time is very high.
This paper includes the implementation of HAMMING-CUT-MATCHING algorithm which reduces the comparison time for matching the iris code with database so that we can use iris recognition in case of huge databases like voting system. As we have used hand geometry for verifying the identified person, it adds the security to the whole system. Finally this paper contains the applications of the combined features of the recognition of iris and verification of hand geometry in airport.
BIOMETRIC SYSTEMS
The determination, measuring, and codification of the unique characteristic traits that each of us is born with is known as the science of biometrics. Various forms of computer-based biometrics for personal authentication have been around for the past twenty years, but not until recently have some reached maturity and a quality/reliability that has enabled their widespread application. In the past, hand geometry enjoyed the advantage of very small templates (codes containing the biometric data), but with modern computers this is no longer the main issue and iris based solutions are steadily gaining ground.
Retinal, iris, and fingerprint recognition are mature technologies with the most reliable performance. Of the three methods, iris recognition is the least intrusive with greater accuracy.
In addition to reliable performance some of the other advantages of using biometrics are:
 High security: It is based on physical characteristics, which cannot be lost or stolen.
 Certainty/accountability: A specific person, not just a holder of a token or somebody who knows a PIN/password, has been authenticated. Users need not worry about someone using their token or PIN code without their knowledge.
 Ease of administration: The problems of handling forgotten PINs/passwords and lost/stolen keys or access cards are eliminated, the benefit is a lot of time and resources saved.
IDENTIFICATION USING IRIS RECOGNITION
Iris recognition is one of the biometric systems which utilize iris patterns as a method of gathering unique information about an individual. It is considered to be one of the most reliable biometrics with some of the lowest false rejection and false acceptance rates and so it is less intrusive.
IRIS :
The iris, the colored portion of the eye, is approximately 11mm (.433 inches) in diameter and consists of several layers and distinct features such as furrows, ridges, coronas, crypts, rings which controls the amount of light that enters into the eye. Varying in shades of brown, blue and green, no two irises are alike, not even within the same individual or identical twins.
PROPERTIES:
Glasses and contact lenses, even colored ones, do not interfere with the process. In addition, recent medical advances such as refractive surgery, cataract surgery and cornea transplants do not change the iris' characteristics. In fact, it is impossible to modify the iris without risking blindness. And even a blind person can participate. As long as a sightless eye has an iris, that eye can be identified by iris recognition.
FINDING IRIS IN AN IMAGE:
An iris has a mesh-like texture to it, with numerous overlays and patterns that can measured by the computer. The camera such as CCD having a high resolution can be set at a distance of four inches (10 centimeters) to 40 inches (one meter), depending on the scanning environment. When iris recognition is used for logging on to a personal computer or checking in at an airport, people need to be somewhat closer to the camera. An automatic cash machine, on the other hand, does not require such nearness.
The iris-recognition software uses about 256 "degrees of freedom," or points of reference, to search the data for a match. The iris is found by using an integrodifferential operator (1), which determines the inner and outer boundaries of the iris's colored pigmentation. Not all of the iris is used: a portion of the top, as well as 45˚ of the bottom, are unused using the masking bits to account for eyelids and camera-light reflections as shown
ENCODING BY 2D WAVELET DEMODULTION :
Each isolated iris pattern is then demodulated to extract its phase information using quadrature 2D Gabor wavelets. It amounts to a patch-wise phase quantization of the iris pattern, by identifying in which quadrant of the complex plane each resultant phasor lies when a given area of the iris is projected onto complex-valued 2D Gabor wavelets. Such a phase quadrant coding sequences. A desirable feature of the phase code is that it is a cyclic, or grey code: in rotating between any adjacent phase quadrants, only a single bit changes, unlike a binary code in which two bits may change, making some errors arbitrarily more costly than others. Altogether 2,048 such phase bits (256 bytes) are computed for each iris, but in a major improvement over the earlier algorithms, now an equal number of masking bits are also computed to signify whether any iris region is obscured by eyelids, contains any eyelash occlusions, specular reflections, boundary artifacts of hard contact lenses, or poor signal-to-noise ratio and thus should be ignored in the demodulation code as artifact. Thus an iris pattern is converted into a sequence of phasor bits which can be stored in the iris recognition software and then can compared for its identification.