Iris Recognition

John Daugman • There is only one iris recognition algorithm in use • The algorithm was developed mainly by John Daugman, PhD, OBE • www.CL.cam.ac.uk/users/jgd1000/ • It is owned by the company Iridian Technologies

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

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

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

Gabor Wavelets

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

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

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

Hamming Distance

HD



No.

of bits different Total no.

of bits

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

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

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

Disadvantages of the Iris for Identification

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Small target (1 cm) to acquire from a distance (1 m)

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Moving target ...within another... on yet another

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Located behind a curved, wet, reflecting surface

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Obscured by eyelashes, lenses, reflections

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Partially occluded by eyelids, often drooping

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Deforms non-elastically as pupil changes size

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Illumination should not be visible or bright

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Some negative (Orwellian) connotations

Fake Iris Attacks

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