a novel aproach towards template reduction in recognition of human iris

1. TEMPLATE REDUCTION IN HUMAN IRIS
PATTERNS RECOGNITION
Presented by:
N.Ishwarya
13701A0432
Annamacharya Institute Of Technology and Sciences

2. CONTENTS
 Motivation
 History
 Introduction to Iris Recognition
 Why IRIS Recognition??
 Structure Of Eye
 Stages
 Template in IRIS Recognition
 Why template reduction is necessary??
 Experimental Results
 Advantages
 Conclusion
 References

3. 1.MOTIVATION
 Authentication: The process of verifying that a user
requesting a resourse is who he,she or it claims to
be,and vice versa.

4. CONVENTIONAL AUTHENTICATION
METHODS
 “Some thing that you have”-key, magnetic card or
smart card.
 “Some thing you know”-PIN or Password.

5. BIOMETRIC AUTHENTICATION-”SOME THING
THAT YOU ARE”

6. 2.HISTORY
 Iris Recognition system was first proposed by
‘FLOM and SAFIR’ in 1987
 In year 1994,JOHN DAUGMAN patented his
"Biometrics Personal Identification System Based
On Iris analysis”

7. INTRODUCTION TO IRIS RECOGNITION

8. WHY IRIS RECOGNITION
 Iris patterns are Unique
 They do not change with age
 Non contact approach
 Simplicity and ease of implementation.
 Speed –the process of matching the Iris patterns is
very fast.

9. STRUCTURE OF IRIS
 Iris is a flat, coloured, ring-shaped membrane
behind the cornea of the eye, with an adjustable
circular opening (pupil) in the centre.
 It is embedded with tiny muscles that control the
amount of light entering into Eye through Pupil.

10. STAGES OF IRIS RECOGNITION

11. STAGE 1:
Image Acquisition:
The purpose of this stage is to capture a high
quality image of the eye

13. STAGE 2:
 Iris Localisation:
The Purpose of this stage to localise that portion of
acquired image that corresponds to an iris.

15. STAGE 3:
Iris Normalisation:
The normalisation process will introduce two
iris regions, which have the same constant
dimensions, so that two photographs of Iris
under different conditions will have same
characteristic features.

16. STAGE4&5:
 4.Feature Extraction:
In this stage, we generate a template code along with
a mask code.
 5.Pattern Matching:
Compare two iris templates using hamming distances
: to counter rotational inconsistencies.

17. TEMPLATE IN IRIS RECOGNITION
The templates are fully functional programs.
In IRIS RECOGNITION SYSTEM the templates are
operated through MATLAB.
You can access the templates in two ways: From
the MATLAB® tool strip, on the HOME tab, in the
FILE section, select New > Graphical User
Interface. If the Layout Editor is already open,
select File > New.

19. WHY....TEMPLATE REDUCTION??
 Currently ,Iris template size is 20 x 480
 Through this, the recorded pattern will be in
accurate
 In order to avoid this, template size is reduced to 10
x 480.
 There will be no computation losses followed by
accuracy in pattern.

20. EXPERIMENTAL RESULTS
 Reduction in size from 20 x 480 to 10 x 480 give an
encourage result in a successful experimentation
through reduction of size will have lesser
complexity and better accuracy.
Neural network tool Dimensions (template) Template 1&2
Hamington distance 20 x 480 0.3418
10 x 480 0.2655
10 x 240 0.324

21. PROS AND CONS
Pros:
 More accurate
 Highly protected
 Smaller template size so that data bases can be
easily stored and checked.
Cons:
 People who had undergone laser treatment
may get a bit stressed and head ache.

22. CONCLUSION
“Better security for better future”-the present
generations motto..
This iris recognision creates new trends in bio-
metrics.
Hope this method of reduction of template will create
an evolution.

24. ITS YOUR TURN....