Biometrics & Security
Tutorial 7
• 1 (a) Please compare two different
kinds of biometrics technologies:
Retina and Iris. (P8:2-3)
•
1 (b) Understand the retina
recognition system. Please give the
differences between retinal
identification and retinal
authentication. (P8: 10-11)
• 1 (c)P8:20 show a representative
example of identification system.
Please give another example of
verification system.
•
1 (d) Please understand the iris
recognition system. (P8: 22-36)
•
1 (e) What is texture feature (P8: 30)?
Why we can use texture feature in iris
recognition (P8: 31)?
•
2. There are four steps in the
Daugman’s approach (P8: 32-36). The
third step generates IrisCode with 512
bytes. If 2 bits represent a feature,
please compute the total number of
features. (512*(8/2)=2,048)
• Hamming distance: the distance between
two vectors A and B is ∑ | Ai - Bi |.
General idea of Iris Code
•
•
•
•
•
3. In P8:37, an example of iris verification
distributions is given. Notice that Hamming
distance is defined to measure the
similarity of two IrisCodes.
Which value in the figure can separate two
parts, authentics and imposters?
If the similarity between two IrisCodes is
taken as 0.5, can you say they are identical?
How about the comparison result when the
similarity is 0.2?
What conclusion will you get from the
hamming distance used to compute
similarity of IrisCodes? (0.38; no; yes)
True Acceptance Rate
• A genuine individual is accepted. (TAR)
TAR 
Total True Acceptance
Total True Attempts
Threshold=0 means that the
attempts whose matching
score >0 will be accepted;
(everybody will be accepted)
1
TAR
0
Threshold (Matching scores)

Threshold=∞ means that
the attempts whose
matching score > ∞ will be
accepted
(nobody will be accepted)
False Rejection Rate
• A genuine individual is rejected. (FRR)
Total False Rejection
FRR 
Total True Attempts
Threshold=0 means that
the attempts whose
matching score <0 will be
rejected;
(nobody will be rejected)
1
FRR
0
Threshold (Matching scores)

Threshold=∞ means that
the attempts whose
matching score < ∞ will be
rejected
(everybody will be rejected)
True Rejection Rate
• A impostor is rejected. (TRR)
TRR 
Total True Rejection
Total False Attempts
Threshold=0 means that
the attempts whose
matching score <0 will be
rejected;
(nobody will be rejected)
1
TRR
0
Threshold (Matching scores)

Threshold=∞ means that
the attempts whose
matching score < ∞ will be
rejected
(everybody will be rejected)
False Acceptance Rate
• A impostor is accepted. (FAR)
FAR 
Total False Acceptance
Total False Attempts
Threshold=0 means that the
attempts whose matching
score >0 will be accepted;
(everybody will be accepted)
1
FAR
0
Threshold=∞ means that
the attempts whose
matching score > ∞ will be
accepted
(nobody will be accepted)
Threshold (Matching scores)

ROC
• There are some trade off among TAR, FRR,
TRR, FAR.
• We need a particular threshold to keep the TAR
and TRR as high as possible and to keep FAR
and FRR as low as possible.
• We need the ROC curve to find the optimal
threshold.
• We also use ROC curve to evaluate the system
ROC(2)
Find the optimal point (threshold)
ROC Curve
ROC Curve
1
1
TAR
FAR
0
FAR
1
0
FRR
1
•
4. P8:27 shows the corresponding
Fourier transforms of iris images with
different quality. Please give the
property of Fourier transform of good
quality iris images. (Even distribution)
Fourier Transform
• Any signal can be expressed as a weighted sum of a series of sine
or cosine wave
• a is the original signal
• a = w1∙b + w2∙b + w3∙d
• b is a low frequency component
• d is a high frequency component
A sum of sines and cosines
=
3 sin(x)
A
+ 1 sin(3x)
B
+ 0.8 sin(5x)
C
+ 0.4 sin(7x)
D
A+B
A+B+C
A+B+C+D
• 5. In Daugman’s approach iris is
regarded as a circular pattern (P8: 3236). In fact we can also take the iris as
other pattern, as shown in P8: 29.
Please try to design the corresponding
scheme.