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IRIS SCANNING

AVINASH KUMAR GUPTA

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Contents

Overview of biometrics
History
Introduction
Biometrics And Iris Scanning
Iris Recognition systems
Four simple steps to follow
Architecture
Working of iris technology
Image Acquisition
Preprocessing

Iris Localization
Edge Detection

Image Analysis
Image Recognition

Recording of Identities
Pattern Matching
Advantages of iris technology
Disadvantages of iris technology
Applications of iris Recognition

system

Real Life Applications
Comparison Of Iris Recognition With Other Biometrics
Conclusion
References

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Overview of biometrics

Biometrics is the science of measuring physical or anatomical characteristics of individuals.
It performs automatic identification of a person based on his/her physiological characteristics.
Among the features measured are face, fingerprints, handwriting, iris, retinal, vein, and voice. Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions.
Of all the biometric devices and scanners available today, it is generally conceded that iris recognition is the most accurate. The automated method of iris recognition is relatively young, existing in patent since only 1994.

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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 Doug man 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

When

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The iris is a Protective internal organ of the eye. It is easily visible from yards away as a colored disk, behind the clear protective window of the cornea, surrounded by the white tissue of the eye. It is the only internal organ of the body normally visible externally. It is a thin diaphragm stretching across the anterior portion of the eye and supported by lens.

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.”

What is Iris?

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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.

WHY

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Biometrics And Iris Scanning

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Iris Recognition systems

Iris recognition is fast developing to be a full proof and fast identification technique that can be administered cost effectively. It is a classic biometrics application that is in an advanced stage of research all over the world.
Iris cameras perform recognition detection of a person’s identity by mathematical analysis of the random patterns that are visible within the iris of an eye from some distance. It combines computer vision, pattern recognition, statistical inference and optics.

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FOUR SIMPLE STEPS TO FOLLOW

A person stands in front of the iris identification system, between one or three feet away, while a wide angle camera calculates the position of their eye.
A second camera zooms in on the eye and takes a black and white image.
Once the iris is in focus, it overlays a circular grid on the image of the iris and identifies the light and dark areas, like an “eye print”.
To prevent a fake eye from being used to fool system, these devices may vary the light shine into the eye and watch for pupil dilation.

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Architecture

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Working of iris technology

The iris identification program may be divided into four main functional blocks:

Image Acquisition.
Preprocessing.
Image Analysis.
Image Recognition.

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Image Acquisition

To acquire images with sufficient resolution and sharpness to support recognition.
Good contrast and high illumination.
Optics and Camera:
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.
Camera Distance up to 3 meters.
High Quality Image, Daughman’s Algorithm expect minimum 640X480.

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In order to accomplish this, we use a CCD camera. We set the resolution to 640x480, the type of the image to jpeg, and the mode to white and black for greater details. The camera is situated normally between half a meter to one meter from the subject. (3 to 10 inches)

BLOCK DIAGRAM OF IMAGE ACQUISITION USING CCD CAMERA

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Preprocessing

The acquired image always not only “useful” parts (IRIS), but also some “irrelevant” parts e.g. eyelid, pupil .
Preprocessing removes the effect of spots/holes lying on the pupillary area.
The Preprocessing module first transforms the true colour into intensity image

So the preprocessing is composed of two steps:

Iris Localization
Edge Detection

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Iris Localization

Iris localization is a process that delimits the iris from the rest of the acquired image. After the camera situates the eye, the Daugman’s algorithm narrows in from the right and left of the iris to locate its outer edge.
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.

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Edge Detection

It is used to find complex object boundaries by marking potential edge point corresponding to places in an image where rapid change in brightness occurs.
In other words, edge is defined by the discontinuity in gray values. An edge separates two distinct objects.

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Canny Edge Detector

Canny Edge Detector finds edges by looking for the local maxima of the gradient of the input image. It calculates the gradient using the derivative of the Gaussian filter. The Canny method uses two thresholds to detect strong and weak edges. It includes the weak edges in the output only if they are connected to strong edges. As a result, the method is more robust to noise, and more likely to detect true weak edges.

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Process of Canny Edge detector

1: filtering image with derivative of gausian.

2. finding magnitude and orientation of image.

3. Apply non-maximum suppression

4. linking and thresholding

Defies two thresholds Low and high
Use the high threshold to start edge curve and the low threshold to continue them

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HOUGH TRANSFORM

(1) an eye image (2) corresponding edge map (3) edge map with only horizontal gradients I4) edge map with only vertical gradients.

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Image Analysis

The features of the iris are then analyzed and digitized into a 512 byte (4096 bits) Iris Code record.

In this iris code half of the describes the features and another half of the describes the control the comparison process.

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Image Recognition

Iris code record is stored in the

database for future comparison.

During a recognition attempt, when an

iris is presented at a recognition point,

the same process is repeated ; however

the resulting Iris Code record is not

stored but is compared to every file

in the database.

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Recording of Identities

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The Process Overview:

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Pattern Matching

The produced code matches the encoded features stored in the database.

One technique for comparing two Iris Codes

is to use the Hamming distance, which is

the number of corresponding bits that differ

between the two Iris Codes.

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Advantages of iris technology

Highly protected, internal organ of the eye.
Stability : Persistence of iris patterns.
Search speed: 100,000 Iris Codes per second
Unique - the probability of two rises producing the same code is nearly impossible.
Flexible - iris recognition technology easily integrates into existing security systems or operates as a standalone
Patterns apparently stable throughout life.
Reliable - a distinctive iris pattern is not susceptible to theft, loss or compromise

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Disadvantages of iris technology

Small target (1 cm) to acquire from a distance (1m)
Alcohol consumption causes deformation in Iris pattern
Illumination should not be visible or bright
Obscured by eyelashes, lenses, reflections
It will be difficult to capture an image of handicap people sitting on wheel chair because the cameras are usually attached on the wall and capture an image up to a certain height.
The iris recognition systems are much costlier than other biometric technologies.
If a person is wearing glasses or facing direct sunlight for quite a while, than it may affect the authentication.

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Applications of iris Recognition system

Computer login: the iris as a living password.
National border controls: the iris as a living passport.
Driving licenses and personal certificates.
Internet security, control of access to privileged information.
Premises access control (Home, Office, Laboratory).
Anti-terrorism (e.g. security screening at airports)
Financial Transactions (electronic commerce and banking).
Secure accesses to bank cash machine accounts.
Credit-card authentication.
Automobile ignition and unlocking; anti-theft devices

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Real Life Applications:

Aadhaar India's Unique ID project for its one billion citizens uses Iris scan as one of the identification features.
United Arab Emirates uses it in border patrol.
Permits passport free immigration in several countries like Netherlands, Canada, US.
Google uses iris scanners to control access to their datacenters.

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Comparison Of Iris Recognition With Other Biometrics

Accurate
Stability
Fast
Scalable

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Comparison

Method	Coded Pattern	MisIdentific --ation rate	Security	Applications
Iris	Iris pattern	1/1,200,000	High	high-security
Fingerprint	fingerprints	1/1,000	Medium	Universal
voice	Voice characteristics	1/30	Low	Telephone service
Signature	Shape of letters, writing Order, pen pressure	1/100	Low	Low-security
Face	Outline, shape & distribution of eyes, nose	1/100	Low	Low-security
Palm	size, length, & thickness hands	1/700	Low	Low-security

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Iris recognition system is also finding unexpected applications. The best know example involved using iris recognition to confirm the identification of a mysterious young afghan woman named Sharbat Gula originally photographed by Steve McCurry in 1984.Some 18 years later, McCurry photographed Sharbat Gula in Afghanistan .At the behest of National Geographic, Dr.John Dougman,developer of the Iris recognition system, then compared the irises in the photographs using his algorithms. He concluded that the eyes were a match.

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Conclusion

The applications of iris recognition are rapidly growing in the field of security, due to it’s high rate of accuracy. This technology has the potential to take over all other security techniques, as it provides a hands-free, rapid and reliable identification process.
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.

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References