Iris Recognition: Mahendra Kumaresh.s

IRIS RECOGNITION The future of identity

by,

Mahendra Kumaresh.S

Biometric Technology •Verifies/Recognizes identity of a living person. •Eg:- Iris recognition, face recognition, fingerprint, voice recognition etc. •Tremendous accuracy and speed. •Provides high level of security for sensitive information. •Helps prevent fraudant use of ATM’s etc.

Biometric

devices have 3 primary components

4. Mechanism to capture image of a living personal characteristic. 6. Compression ,processing ,storage and comparison of image with stored data. 8. Interfaces with application systems.

•A biometric system can be divided into 2 stages : 3. Enrolment Module. 5. Identification Module. •

During the enrolment stage:

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Biometric sensor scans the person’s physiognomy to create a digital representation.

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A feature extractor processes the representation to generate a template.

•During the identification stage: •Biometric sensors capture the characteristics of person to be identified. •Converts it into the same format as the template. •The resulting template is fed into a feature matcher. •Feature matcher compares it against the stored template to determine whether the two templates match.

Cost and Accuracy •Cost is directly related to accuracy and vice-versa.

IRIS RETINA COSTSIGNATURE FINGER FACE VOICE ACCURACY

The Human Iris •The iris is a membrane in the eye, responsible for controlling the amount of light reaching the retina .

•The pupil is a circular opening located in the center of the iris of the eye. •The white outer area is the sclera. the central transparent part of which is the cornea.

•The unique pattern on the surface of the iris is formed during the first year of life. •Formation of the unique patterns of the iris is random and not related to any genetic factors. •Due to the epigenetic nature of iris patterns, identical twins possess uncorrelated iris patterns. •The two eyes of an individual contain completely independent iris patterns.

IRIS RECOGNITION •The process of identifying a person by analyzing the pattern of the iris. •Provides an unmatched identification technology. •Uses highly accurate algorithms with very little chance of occurrence of error. •Used in large scale identification implementations.

History of Iris Recognition • It was in the early nineties that Cambridge researcher, John Daugman, implemented a working automated iris recognition system • The Daugman system is patented and the rights are now owned by the company Iridian Technologies(1994). • Zero failure rate • Perfectly identifies a person given millions possibilities.

Why IRIS? •Data rich physical structure about 400 identifying features •Genetic independence •Stability over time •Inherent isolation and protection from external environment. •Impossibility of surgically modifying it. •Its physiological response to light.

Design and Implementation

Block diagram of Iris Recognition system

•The design and implementation of the system is subdivided into 3: 3. Image acquisition 4. Iris localization 5. Patter Matching

Image Acquisition •Capturing of high quality images of the iris. •Wide angle cameras are used. •LED based point light sources are used for illumination. •The operator positions in front of the camera. •At a distance of not more than 1m.

•The operator is provided with a live video feed. •Allowing the operator to see what the camera is capturing. •Once a series of images are captured it is automatically forwarded .

3 important requisites : •

Images of the iris with sufficient resolution and sharpness to support recognition.

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Good contrast in the interior iris pattern.

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Images must be well framed .

Iris Localization •

Delimits the iris from the rest of the acquired image

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Daugman’salgorithm is used to narrow in from the right and left of the iris to locate its outer edge.

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Iris recognition technology converts the visible characteristics of the iris into a 512 byte Iris Code

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Future comparisons are based on the Iris Code

Iris Localization

Pattern Matching •Evaluates the goodness of match between the newly acquired iris pattern and the candidate’s data base entry. •Hamming Distance - fraction of mismatched bits •We use one-to-many search of database •The entire process takes about 2 seconds.

Accuracy •Accuracy higher than other forms of biometrics. •Odds of returning 75% match- 1 in 10^16 •Equal error rate

1 in 12 million

•Odds of identical iris codes-1 in 10^52

Independence of bits across iris codes •No systematic correlation between different irises. •Probability that bits in different position are set to 1 .

•Distribution hovers over .5

•All bits are equally likely to be 0 or 1. •Hence we can infer that is no systematic Correlation between irises.

Advantages •Small error rates (EER) or high 'accuracy‘. •No failure to enroll (FTE) . •Easy for someone to use, not intrusive . •Fast verification, fast identification (1,00000 /sec). •Robust against 'countermeasures' and fraud . •Social acceptance .

Comparison with other biometric technologies

A-Excellent

D-Poor

Iris Recognition:Issues

•The technology requires a certain amount of user interaction. •Unusual lighting situation may affect the ability of the camera to acquire its subject. •Backup must be in place if the unit becomes inoperable. •But these issues do not affect the effectiveness of the technology

Applications •ATM’s •Tracking prisoner movement •Computer Login •Ticket less travel •Driving license and other personal certificates. •Mobile phones.

•Tracking of missing or wanted persons •Credit card authentication •Anti –terrorism( eg :- screening at airports etc) •Secure financial transaction

Conclusion •As iris technology grows less expensive, it could very likely unseat a large portion of the biometric industry. •Its technological superiority has already allowed it to make significant inroads into identification and security venues which had been dominated by other biometrics •Iris-based biometric technology has always been an exceptionally accurate one, and it may soon grow much more prominent.

THANK YOU