The document discusses iris biometrics for identification. It describes the retina and iris, noting that the unique patterns of blood vessels and iris are highly distinctive even between identical twins. Iris recognition involves using cameras to capture high-resolution photos of the iris within a few feet. Software then locates the iris boundaries, normalizes it, and encodes the pattern to generate an iris code for identification purposes by comparing to stored templates. The iris remains stable over a lifetime but can be affected by some eye diseases. Compared to other biometrics, iris scanning is accurate, stable, fast, and scalable for identification.

1. IRIS BIOMETRICS

3. Retina
•The retina is a thin layer of cells at the back of the eyeball.
•It is the part of the eye which converts light into nervous signals.
•The unique structure of the blood vessels in the retina has been used for biometric identification.
•Retina recognition technology captures and analyzes the patterns of blood vessels on the thin
nerve on the back of the eyeball that processes light entering through the pupil. Retinal patterns
are highly distinctive traits.
•Every eye has its own totally unique pattern of blood vessels; even the eyes of identical twins are
distinct. Although each pattern normally remains stable over a person’s lifetime, it can be affected
by disease such as glaucoma, diabetes, high blood pressure, and autoimmune deficiency
syndrome.

4. IRIS
Iris is the area of the eye where the pigmented or colored circle, usually brown, blue, rings the
dark pupil of the eye.

5. Normal Eye Example of Irish

6. Example of 10 Different People Iris

7. Iris Recognition systems
The iris-scan process begins with a photograph. A specialized camera, typically very close to the
subject, not more than three feet, uses an infrared imager to illuminate the eye and capture a very
high-resolution photograph. This process takes 1 to 2 seconds.

8. Creating an Iris code
•The picture of eye first is processed by software that localizes the inner and outer boundaries of the iris.
•And it is encoded by image-processing technologies.
•In less than few seconds, even on a database of millions of records, the iris code template generated from a
live image is compared to previously enrolled ones to see if it matches to any of them.

9. Characteristics of Iris recognition
Iris is thin membrane on the interior of the eyeball.
Iris pattern remains unchanged after the age of two and does not degrade overtime or with the
environment.
Iris patterns are extremely complex than other biometric patterns.

10. Typical iris system configuration for taking a picture
An iris recognition camera takes a black and white picture from 5 to 24 inches away.
The camera uses non-invasive, near-infrared illumination that is barely visible and very safe.
And this iris recognition cannot take place without the person permission

14. An Iris Recognition Process

15. Techniques used
Iris Localization
Iris Normalization
Image Enhancement

16. Iris Localization
 Both the inner boundary and the outer boundary of a typical iris can be taken as circles. But the
two circles are usually not co-centric. Compared with the other part of the eye, the pupil is much
darker. We detect the inner boundary between the pupil and the iris. The outer boundary of the iris
is more difficult to detect because of the low contrast between the two sides of the boundary. We
detect the outer boundary by maximizing changes of the perimeter- normalized along the circle.
The technique is found to be efficient and effective.

17. Iris Normalization
The size of the pupil may change due to the variation of the illumination and the associated
elastic deformations in the iris texture may interface with the results of pattern matching. For the
purpose of accurate texture analysis, it is necessary to compensate this deformation. Since both
the inner and outer boundaries of the iris have been detected, it is easy to map the iris ring to a
rectangular block of texture of a fixed size.

18. Image Enhancement
The original image has low contrast and may have non-uniform illumination caused by the
position of the light source. These may impair the result of the texture analysis. We enhance the
iris image reduce the effect of non-uniform illumination.

19. Image Enhancement
The original image has low contrast and may have non-uniform illumination caused by the
position of the light source. These may impair the result of the texture analysis. We enhance the
iris image reduce the effect of non-uniform illumination.

20. Iris preprocessing: (a) original eye (b) iris localization
( c ) iris normalization (d) image enhancement

21. Comparison Of Iris Recognition With
Other Biometrics
 Accurate
 Stability
 Fast
 Scalable

23. Reference
Y.Zhu,T.Tan and Y.Wang,”Biometric Identification Based on Iris Pattern”.
Anil K Jain,”Biometric Authentication: How Do I Know Who You Are”.
D Maltoni, D.Maio, Anil K Jain, and S prabhakar”Handbook of Finger print Recognition”.