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IRIS Biometric for Person Identification. By Lakshmi Supriya.D

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Iris biometric for person identification

IRIS Biometric for Person Identification

By

Lakshmi Supriya.D

M.Tech 04IT6002

Dept. of Information Technology


Iris biometric for person identification


Iris biometric for person identification
Iris Identification

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


Iris biometric for person identification

Example of iris Identification

Normal Eye



Exciting biometrics
Exciting Biometrics Identification

  • Fingerprint Recognition

  • Voice Recognition

  • Signature Recognition

  • Face Recognition

  • Palm Recognition


Fingerprint recognition
Fingerprint Recognition Identification

  • This relies on the fact that a fingerprint’s uniqueness can be defined by analyzing the minutiae of a human being.

  • Two individuals having the same fingerprint is less than one in a billion.


Voice recognition
Voice Recognition Identification

  • The person to be identified is usually pronounce a designated password or phrase, which facilitates the verification process.

  • But has the weakness of technology


Signature recognition
Signature Recognition Identification

  • This is done by analyzing the shape, speed, stroke, pen pressure and timing information during the act of signing.

  • Dynamic signature verification is a replacement.


Face recognition
Face Recognition Identification

  • To identify any person we generally look at face and eyes in particular seem to tell a story how the person feels.

  • Face recognition is a kind of electronic unmasking


Palm recognition
Palm Recognition Identification

  • The image of the hand is collected and the feature vectors are extracted and compared with the database feature vectors.


Iris recognition systems
Iris Recognition systems Identification

  • 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.


Creating an iris code
Creating an Iris code Identification

  • 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
Iris recognition Identification

  • 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.


Major characteristics of iris recognition
Major characteristics of iris recognition Identification

  • 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


Typical iris system configuration for taking a picture
Typical iris system configuration for taking a picture Identification

  • 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


Example of iris recognition system
Example of iris recognition system Identification

Gate device

Management device

reference

Register

Lan


Typical iris system configuration
Typical iris system configuration Identification

Uniform distribution

Stored templates

Reject

Pre processing

Feature-extraction

Identification Verification

Accept

Iris scan 2d image capture

Iris localization

Transform representation

comparison

enrolment

Authentication


Techniques used
Techniques used Identification

  • Iris Localization

  • Iris Normalization

  • Image Enhancement


Iris localization
Iris Localization Identification

  • 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.


Iris normalization
Iris Normalization Identification

  • 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.


Image enhancement
Image Enhancement Identification

  • Theoriginal 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.


Iris biometric for person identification

Iris preprocessing: (a) original eye (b) iris localization Identification

( c ) iris normalization (d) image enhancement


Comparison of iris recognition with other biometrics
Comparison Of Iris Recognition With Other Biometrics Identification

  • Accurate

  • Stability

  • Fast

  • Scalable


Comparison
Comparison Identification

MisIdentific--ation rate

Security

Applications

Method

Coded Pattern

1/1,200,000

Iris pattern

High

high-security

Iris

fingerprints

Fingerprint

Medium

1/1,000

Universal

Voice characteristics

voice

Low

1/30

Telephone service

Shape of letters, writing

Order, pen pressure

Signature

Low

Low-security

1/100

Outline, shape & distribution of eyes, nose

Face

1/100

Low

Low-security

size, length, & thickness hands

Low

Palm

1/700

Low-security


Analysis
Analysis Identification

  • Current Uses

  • Future Uses


References
References Identification

  • 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”.