IRIS RECOGNITION

The need for biometrics

As per wikipedia, “Biometrics consists of methods for uniquely recognizing humans

based upon one or more intrinsic physical or behavioral traits”

The need for biometricso -> Rapid development in technologyo -> Globalization

Biometrics and Iris Scanning

Anatomy of the Human Eye

• Eye = Camera

• Cornea bends, refracts, and focuses light.

• Retina = Film for image projection (converts image into electrical signals).

• Optical nerve transmits signals to the brain.

What is Iris?5

The coloured ring around the pupil of the eye is called the iris ,like a snowflake.

Controls light levels inside the eye. Tiny muscles that dilate and constrict the pupil size. Divides the front of the eye from the back of the eye. Color comes from melanin.

brown or black in colour

Individuality of Iris

Left and right eye irises have distinctive pattern.

Characteristics of Iris7

Has highly distinguishing texture. Right eye differs from left eye. 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.

What Is It?

.

Going the layman way the biometric identification of the iris is called as “IRIS SCANNING”.

But as per WIKIPEDIA, “Iris recognition is a method of biometric authentication that uses

pattern-recognition techniques based on high-resolution images of the irides of an individual's eyes.”

WHY ?

The iris is a living password

Artificial duplication is virtually impossible

400 identifying features

Probability of matching of two irises is 1:1078

Genetic independency

Its inherent isolation and protection from the external environment.

WHEN

1936

• Idea was proposed by ophthalmologist Frank Burch

1980

• Appeared in the Bond Films

1987• Aram Safir & leonard Flom patented the idea and asked John

Dougman to create actual algorithms for that. John Dougman created this algorithm and patented that in the same year..

1987

• Licensee Sensar deployed special cameras in ATMs of NCR corps and Diebold Corps

1997-1999

• “Panasonic Authenticam” was ready for use in public places like airports

HOW : THE SCIENCE BEHIND IT

To acquire images with sufficient resolution and sharpness to support recognition.

A. Optics and Camera: Human heads are on the order of 15 cm wide. In case of a portal, we needed a capture volume width on the order of 20–30 cm. More than 200 pixels or more across the iris- Good quality. Of 150–200 pixels across the iris – Acceptable quality Of 100–150 pixels to be of- Marginal quality.

B. Illumination: The shutter is only open during the strobe to reduce the effect of ambient light.

C. Coarse Segmentation: Daugman algorithm expects 640 x 480 images.

Iris on the Move: Acquisition of Images

Iris Localization  13

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.

  

Iris Normalization  14

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.   

How closely the produced code matches the encoded features stored in the database.

One technique for comparing two IrisCodes is to use the Hamming distance, which is the number of corresponding bits that differ between the two IrisCodes.

Pattern Matching

Recording of Identities

Image Processing

John Daugman (1994)

• Pupil detection: circular edge detector

• Segmenting sclera

0000

,,,, 2

),()(max

yxryxr

dsr

yxI

rrG

Rubbersheet Model

rr

0 1

θ

θEach pixel (x,y) is mapped into polar pair (r, ).

Circular band is divided into 8 Sub-bands of equal thickness for a given angle .

θ

θ

Measure of Performance

• Off-line and on-line modes of operation. Hamming distance: standard measure for comparison of binary strings.

k

n

kk yx

nD

1

1

x and y are two IrisCodes

is the notation for exclusive OR (XOR)

Counts bits that disagree.

Observations

• Two IrisCodes from the same eye form genuine pair => genuine Hamming distance.

• Two IrisCodes from two different eyes form imposter pair => imposter Hamming distance.

• Bits in IrisCodes are correlated (both for genuine pair and for imposter pair).

• The correlation between IrisCodes from the same eye is stronger.

Iris Recognition System

LocalizationAcquisition

IrisCode Gabor Filters Polar Representation

Image

Demarcated Zones

22

Imaging Systemshttp://www.iridiantech.com/

· Highly protected, internal organ of the eye· Externally visible; patterns imaged from a distance· Iris patterns possess a high degree of randomness .Uniqueness: set by combinatorial complexity · Changing pupil size confirms natural physiology· Limited genetic penetrance of iris patterns· Patterns apparently stable throughout life.A key advantage of iris recognition is its stability, or template

longevity, as, barring trauma, a single enrollment can last a lifetime.

Merits

Demerits

· Small target (1 cm) to acquire from a distance (1m)· Located behind a curved, wet, reflecting surface· Obscured by eyelashes, lenses, reflections· Partially occluded by eyelids, often drooping· Deforms non-elastically as pupil changes size· Illumination should not be visible or bright.

Applications

. ATMs .Fugitive track record .Computer login: The iris as a living password. · National Border Controls: The iris as a living password. · Ticket less air travel. · Premises access control (home, office, laboratory etc.). · Driving licenses and other personal certificates. · Entitlements and benefits authentication. · Forensics, birth certificates, tracking missing or wanted person · Credit-card authentication. · Automobile ignition and unlocking; anti-theft devices. · Anti-terrorism (e.g.:— suspect Screening at airports) · Secure financial transaction (e-commerce, banking). · Internet security, control of access to privileged information.

National Geographic: 1984 and 2002

Sharbat Gula

The remarkable story of Sharbat Gula, first photographed in 1984 aged 12 in a refugee camp in Pakistan by National Geographic (NG) photographer Steve McCurry, and traced 18 years later to a remote part of Afghanistan where she was again photographed by McCurry.

So the NG turned to the inventor of automatic iris recognition, John Daugman at the University of Cambridge.

The numbers Daugman got left no question in his mind that the eyes of the young Afghan refugee and the eyes of the adult Sharbat Gula belong to the same person.

John Daugman and the Eyes of Sharbat Gula

Iris is seen as the saviour of the UID project in India.

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.

Comparison

Method Coded PatternMisIdentific--ation rate

Security

Applications

Iris Iris pattern 1/1,200,000

High high-security

Fingerprint

fingerprints 1/1,000

Medium Universal

voice

Signature

Face

Palm

Voice characteristics 1/30 Low

Low

Low

Low

Telephone service

Low-security

Low-security

Low-security

1/100

1/100

1/700

Shape of letters, writing

Order, pen pressureOutline, shape & distribution of eyes, nose

size, length, & thickness hands

Conclusion32

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.

References

· http://www.cl.cam.ac.uk·http://en.wikipedia.org/wiki/Iris_recognition .www.seminars4u.comDaugman J (1999) "Biometric decision landscapes."

Technical Report No TR482, University of Cambridge Computer Laboratory.

International Journal of Computer Technology and Electronics Engineering (IJCTEE) Volume 2, Issue 1

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