1. Iris Recognition

3. John Daugman There is only one iris recognition algorithm in use
The algorithm was developed mainly by John Daugman, PhD, OBE
It is owned by the company Iridian Technologies

4. Advantages of Iris Recognition
Irises do not change with age – unlike faces
Irises do not suffer from scratches, abrasions, grease or dirt – unlike fingerprints
Irises do not suffer from distortion – unlike fingerprints

5. Finding the Iris in the Image
It is easy to find the circular boundaries of the iris

6. Masking The boundaries of the eyelids can be found
Eyelashes and specularities (reflections) can be found
These areas can be masked out

7. Gabor Wavelets

8. Gabor Wavelets
Gabor Wavelets filter out structures at different scales and orientations
For each scale and orientation there is a pair of odd and even wavelets
A scalar product is carried out between the wavelet and the image (just as in the Discrete Fourier Transform)
The result is a complex number

9. Phase Demodulation The complex number is converted to 2 bits
The modulus is thrown away because it is sensitive to illumination intensity
The phase is converted to 2 bits depending on which quadrant it is in

11. IrisCodes
This process is carried out at a number of points throughout the image.
The result is 2048 bits which describe each iris uniquely
Two codes from different irises can be compared by finding the number of bits different between them – this is called the Hamming distance
This is equivalent to computing an XOR between the two codes. This can be done very quickly
To allow for rotation of the iris images the codes can be shifted with respect to each other and the minimum Hamming distance found

12. Hamming Distance

13. Binomial Distribution
If two codes come from different irises the different bits will be random
The number of different bits will obey a binomial distribution with mean 0.5

14. Identification
If two codes come from the same iris the differences will no longer be random
The Hamming distance will be less than expected than if the differences were random
If the Hamming distance is < 0.33 the chances of the two codes coming from different irises is 1 in 2.9 million
So far it has been tried out on 2.3 million people without a single error

15. More Advantages of IrisCodes
IrisCodes are extremely accurate
Matching is very fast compared to fingerprints or faces
Memory requirments are very low – only 2048 bits per iris

16. Small target (1 cm) to acquire from a distance (1 m)
Disadvantages of the Iris for Identification
Small target (1 cm) to acquire from a distance (1 m)
Moving target ...within another... on yet another
Located behind a curved, wet, reflecting surface
Obscured by eyelashes, lenses, reflections
Partially occluded by eyelids, often drooping
Deforms non-elastically as pupil changes size
Illumination should not be visible or bright
Some negative (Orwellian) connotations

18. Fake Iris Attacks

19. Fake Iris Fourier Spectrum
Due to the dot matrix grid the Fourier Spectrum of the fake iris has 4 extra points