Iris Recognition: History - 1936 suggested by ophthalmologist
- 1980s James Bond film(s)
- 1986 first patent appeared
- 1994 John Daugman patents new-and-improved technique
Iris Scan - Scanner locates iris
- Take b/w photo
- Use polar coordinates…
- 2-D wavelet transform
- Get 256 byte iris code
Measuring Iris Similarity - Based on Hamming distance
- Define d(x,y) to be
- # of non-match bits / # of bits compared
- d(0010,0101) = 3/4 and d(101111,101001) = 1/3
- Compute d(x,y) on 2048-bit iris code
- Perfect match is d(x,y) = 0
- For same iris, expected distance is 0.08
- At random, expect distance of 0.50
- Accept iris scan as match if distance < 0.32
Iris Scan Error Rate
distance
0.29
|
1 in 1.31010
|
0.30
|
1 in 1.5109
|
0.31
|
1 in 1.8108
|
0.32
|
1 in 2.6107
|
0.33
|
1 in 4.0106
|
0.34
|
1 in 6.9105
|
0.35
|
1 in 1.3105
|
distance
Fraud rate
== equal error rate
- Good photo of eye can be scanned
- Attacker could use photo of eye
- Afghan woman was authenticated by iris scan of old photo
- To prevent attack, scanner could use light to be sure it is a “live” iris
- Equal error rate (EER): fraud == insult rate
- Fingerprint biometrics used in practice have EER ranging from about 10-3 to as high as 5%
- Hand geometry has EER of about 10-3
- In theory, iris scan has EER of about 10-6
- Enrollment phase may be critical to accuracy
- Most biometrics much worse than fingerprint!
- Biometrics useful for authentication…
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