This document discusses biometric security using iris recognition. It begins by introducing iris recognition as a modern and reliable biometric method that is hard to breach and applicable to a wide range. It then provides background on iris recognition, describing its pioneer John Daugman and an example of someone being identified from their iris pattern 18 years later. An overview of the iris recognition system is given which segments the iris region, normalizes variations, extracts features to generate a template, and matches templates using Hamming distance. Results show an accuracy of 82% with an equal error rate of 18.3%. Advantages include iris patterns' uniqueness and stability over time, while concerns include cost and need for the person to be physically present.

1. Guided by: -
Dr. Aditya Abhyankar
By: -
Deepak Attarde
Mayank Gupta
Vishwanath Srinivasan

2. BIOMETRIC SECURITY
 Modern and reliable method
 Hard to breach
 Wide range
 Why Iris Recognition
Highly protected and stable,
template size is small and
image encoding and matching
is relatively fast.

3. INTRODUCTION TO IRIS RECOGNITION
John Daugman, University of
Cambridge – Pioneer in Iris
Recognition.
Sharbat Gula – aged 12 at
Afghani refugee camp.
18 years later at a remote
location in Afghanistan.

4. OVERVIEW OF OUR SYSTEM

5. SEGMENTATION
 Detecting the pupil edges
 Detecting the iris edges
 Extracting the iris region
Canny Edge
Detection
Algorithm

6. NORMALISATION
Daugman’s Rubber Sheet
Model:
(R, theta) to unwrap iris and easily
generate a template code.
Fixed Dimension, Cartesian co-ordinates to Polar co-
ordinates.
Variations in eye: Optical size (iris), position (pupil), Orientation (iris).

7. FEATURE EXTRACTION AND
MATCHING
 Generate a template code along with a
mask code.
 Compare 2 iris templates using
Hamming distances.
 Shifting of Hamming distances: To
counter rotational inconsistencies.
 <0.32: Iris Match
 >0.32: Not a Match

8. RESULTS AND CASE STUDIES
 FAR, FRR
 EER: 18.3 % which gives an accuracy close to 82%
ROC: Receiver Operator
Characteristics

9. Advantages
 Uniqueness of iris patterns hence improved
accuracy.
 Highly protected, internal organ of the eye
 Stability : Persistence of iris patterns.
 Non-invasive : Relatively easy to be
acquired.
 Speed : Smaller template size so large
databases can be easily stored and
checked.
 Cannot be easily forged or modified.

10. Concerns / Possible
improvements
 High cost of implementation
 Person has to be “physically” present.
 Capture images independent of surroundings
and environment / Techniques for dark eyes.
 Non-ideal iris images
Inconsistent Iris size
Pupil Dilation Eye Rotation

11. THANK YOU!!!