Automated Eye-Pattern Recognition Systems 1

What is Iris?.  The colored part of the eye is called the iris.  Its color comes from microscopic pigment cells called melanin. 2

Characteristics of Iris  Has highly distinguishing texture.  Right eye differs from left eye.  Twins have different iris texture.  Twins have different iris texture.  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. 3

Need of Eye-Pattern Recognition Technology  Delusion for Data Privacy.  Passwords, or Social Security Numbers can be broken easily.  Eye pattern recognition system virtually eliminates fake authentication and identity privacy and safely controls authorized entry to sensitive sites, data or material.  Iris Pattern is most distinguished than any other facial feature and do not change overtime and research show the matching accuracy of iris recognition systems is greater than that of DNA testing. 4

Continue…  Iris recognition system is easy to operate, comfortable and is virtually impossible to deceive.  Since the iris is a protected internal organ whose random texture is stable throughout life, it can serve as a living password that one need not remember but one always carries.. 5

Operating Principle  An iris-recognition algorithm first has to identify the approximately concentric circular outer boundaries of the iris and the pupil in a photo of an eye.  The set of pixels covering only the iris is then transformed into a bit pattern that preserves the information that is essential for a statistically meaningful comparison between two iris images.  The mathematical methods used resemble those of modern lossy compression algorithms for photographic images.  In the case of Daugman's algorithms, a Gabor wavelet transform is used in order to extract the spatial frequency range that contains a good signal-to-noise ratio considering the focus quality of available cameras. 6

Continue…  The result is a set of complex numbers that carry local amplitude and phase information for the iris image.  In Daugman's algorithms, all amplitude information is discarded, and the resulting 2048 bits that represent an iris consist only of the complex sign bits of the Gabor-domain representation of the iris image.  Discarding the amplitude information ensures that the template remains largely unaffected by changes in illumination and virtually negligibly by iris color, which contributes significantly to the long-term stability of the biometric template. 7

Continue…  To authenticate via identification or verification, a template created by imaging the iris is compared to a stored value template in a database.  If the Hamming distance is below the decision threshold, a positive identification has effectively been made.  A practical problem of iris recognition is that the iris is usually partially covered by eyelids and eyelashes.  In order to reduce the false-reject risk in such cases, additional algorithms are needed to identify the locations of eyelids and eyelashes and to exclude the bits in the resulting code from the comparison operation. 8

9 Six different images of the same eye. These were 100% verified to be the same eye for every unique combination of 2 images.

10 Six different images of the another eye. These were 80% verified to be the same eye for every unique combination of 2 images. The error is due to the presence of eyelids and eyelashes in the image.

11 Iris Code by John Daugman

An Iris Scan model 2100 iris scanner 12

13 Android Iris Scanner

Procedure  Infrared Eye imaging  Creation of an Iris code  Iris recognition 14

Infrared Eye imaging 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. Creation of 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. Iris recognition 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. 15

Typical iris system configuration for taking a picture  An iris recognition camera takes a black and white picture from 2 to 24 inches away.  The camera uses non-invasive, near-infrared illumination that is barely visible and very safe.  Iris recognition cannot take place without the person permission 16

Techniques used  Iris Localization  Iris Normalization  Image Enhancement 17

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. The inner boundary between the pupil and the iris is detected.  The outer boundary of the iris is more difficult to detect because of the low contrast between the two sides of the boundary.  The outer boundary is detected by maximizing changes of the perimeter- normalized along the circle. 18

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 interfere with the results of pattern matching.  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. 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. 20

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Advantages  Iris is an internal organ which is highly transparent and sensitive membrane. It is more persistent than fingerprints as they tend to fade under manual labor.  Iris is mostly flat, and its geometric configuration is only controlled by two complementary muscles i.e. the sphincter pupillae and dilator pupillae that control the diameter of the pupil. This makes the iris shape far more predictable than the face.  The iris has a fine texture which is determined randomly during embryonic gestation. Even genetically identical individuals have completely independent iris textures, whereas DNA is not unique for the about 0.2% of the human population who have a genetically identical twin.  An iris scan is similar to taking a photograph and can be performed from about 10 cm to a few meters away. 22

Disadvantages  Iris scanning being a new technology is incompatible with most electronic gadgets present.  Iris recognition is very difficult to perform at a distance larger than a few meters and without proper cooperation of the person.  As with other photographic biometric technologies, iris recognition is susceptible to poor image quality.  Equipments used for scanning are very expensive. 23

Deployed applications  United Arab Emirates IrisGuard's Homeland Security Border Control has been operating an expellee tracking system in the United Arab Emirates since 2001, when the it launched a national border-crossing security initiative.  One of three biometric identification technologies internationally standardized by ICAO for use in future passports.  Iris recognition technology has been implemented by BioID Technologies SA in Pakistan for UNHCR repatriation project to control aid distribution for Afghan refugees.  At Schiphol Airport, Netherlands, iris recognition has permitted passport-free immigration since  In a number of US and Canadian airports, as part of the NEXUS program that facilitates entry into the US and Canada for pre- approved, low-risk travelers.  In several Canadian airports, as part of the CANPASS Air program that facilitates entry into Canada for pre-approved, low- risk air travelers. 24

IrisGuard Inc. UAE Enrollment Station 25

A U.S. Marine Corps Sergeant uses an iris scanner to positively identify a member of the Baghdadi city council prior to a meeting with local tribal leaders, sheiks, community leaders and U.S. service members 26

Identifying the Mystery Woman Afghan woman originally photographed by Iris recognition systems are also finding unexpected applications. The best known example involved using iris recognition to confirm the identification of a mysterious young Nation Geographic photographer Steve McCurry in Some 18 years later, McCurry photographed Sharbat Gula in Afghanistan. At the behest of National Geographic, Dr. John Daugman, developer of the iris recognition system, then compared the irides in the photographs using his algorithms. He concluded that the eyes were a match!!! 27

Conclusion  Iris recognition has proven to be a very useful and versatile security measure.  It is a quick and accurate way of identifying an individual with no chance for human error.  Iris recognition is widely used in the transportation industry and can have many applications in other fields where security is necessary.  Iris recognition will prove to be a widely used security measure in the future. 28

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