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IRIS Recognition Technology


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Introduction

Iris Recognition is a Biometric Technology which deals with identification based on the human Iris.
It is considered to be the most accurate biometric technology available today.
Irises can be used to identify individuals rather than just confirm their given identity.

Encoding the Iris

The iris is encoded to a unique set of 2048 bits which serve as the fundamental identification of that person’s particular iris.
These iris bit codes can be stored in a database and then compared to uniquely identify a person.

Final Results

With the batch command line option of the application, it is possible to process a large amount of images of eyes.
Using this option, 108 images of eyes from the database were loaded into the application; the pupil, iris and eyelids were auto-detected to generate a bit code and store it in the database.

Applications

The largest application of iris recognition has been in the aviation industry.
Many of the worlds largest airports like the Heathrow airport of London, employ iris recognition.
The largest use of iris recognition is in United Arab Emirates, where millions of Iris Code comparisons are done each day at all the air, land and sea ports.
Used for Security for government applications.
Used by police departments and government security agencies to keep a record of criminals or suspects.

Conclusion

The Iris technology combines computer vision, pattern
recognition, statistical inference, and optics. Its purpose
is real-time, high confidence recognition of a person’s
identity by mathematical analysis of random patterns
that are visible within iris of an eye from some distance.
Users no longer have to worry about remembering
passwords and system administrators no longer need to
worry about the never-ending problem of users disclosing
passwords or having weak passwords that are easily
cracked.

IRIS Recognition Technology


Introduction

In today’s information technology world, security for systems is becoming more and more important. The number of systems that have been compromised is ever increasing and authentication plays a major role as a first line of defense against intruders. The three main types of authentication are something you know (such as a password), something you have (such as a card or token), and something you are (biometric). Passwords are notorious for being weak and easily crack able due to human nature and our tendency to make passwords easy to remember or writing them down somewhere easily accessible. Cards and tokens can be presented by anyone and although the token or card is recognizable, there is no way of knowing if the person presenting the card is the actual owner. Biometrics, on the other hand, provides a secure method of authentication and identification, as they are difficult to replicate and steal. If biometrics is used in conjunction with something you know, then this achieves what is known as two-factor authentication. Two-factor authentication is much stronger as it requires both components before a user is able to access anything.

Minimum Requirements

At the outset of this project, some key tasks were identified that needed to be carried out to fulfill the aim of creating a working prototype of an iris recognition system. The first task was to read in an image of an eye and display this on screen. From this stage the iris then needs to be isolated from the rest of the image; to do this accurately the pupil, iris, and eyelids all need to be identified. This isolation was originally specified to be carried out manually by the user by clicking points on the image.

Extensions

A number of extensions to these requirements were also proposed in order to increase the effectiveness of the application if time permitted. The most desirable of these was the implementation of a robust method for the automatic detection and isolation of the iris; this would have the effect of reducing the need for user input and hence reduce the margin for error resulting from this to potentially improve the application’s ability to successfully identify an individual.

Methodology

To achieve automated iris recognition, there are three main tasks: first we must locate the iris in a given image. Secondly, it is necessary to encode the iris information into a format which is amenable to calculation and computation, for example a binary string. Finally, the data must be storable, to load and compare these encodings.

Iris Location

When locating the iris there are two potential options. The software could require the user to select points on the image, which is both reliable and fairly accurate, however it is also time consuming and implausible for any real-world application. The other option is for the software to auto-detect the iris within the image. This process is computationally complex and introduces a source of error due to the inherent complexities of computer vision. However, as the software will then require less user interaction it is a major step towards producing a system which is suitable for real-world deployment, and thus became a priority for extending the program specification.

Encoding the Iris

The iris is encoded to a unique set of 2048 bits which serve as the fundamental identi- fication of that person’s particular iris. These iris bit codes can be stored in a database and then compared to uniquely identify a person. The size of 2048 is sufficiently large to store the data of several particular filters on most angles of the iris, while also being sufficiently small to be easily stored in a database and manipulated quickly. We wish to extract phase information from the iris as opposed to amplitude information since phase information is not skewed by pupil deformation. We use Gabor filters to extract this phase information as suggested by Daugman.