Biometrics & Security

1. Biometrics & Security Tutorial 7

2. 1 (a) Please compare two different kinds of biometrics technologies: Retina and Iris. (P8:2-3)

5. 1 (b) Understand the retina recognition system. Please give the differences between retinal identification and retinal authentication. (P8: 10-11)

8. 1 (c)P8:20 show a representative example of identification system. Please give another example of verification system.

11. 1 (d) Please understand the iris recognition system. (P8: 22-36)

18. 1 (e) What is texture feature (P8: 30)? Why we can use texture feature in iris recognition (P8: 31)?

21. 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)

24. Hamming distance: the distance between two vectors A and B is ∑ | Ai - Bi |.

26. General idea of Iris Code

27. 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)

29. True Acceptance Rate • A genuine individual is accepted. (TAR) Threshold=0 means that the attempts whose matching score >0 will be accepted; (everybody will be accepted) Threshold=∞ means that the attempts whose matching score > ∞ will be accepted (nobody will be accepted)

30. False Rejection Rate • A genuine individual is rejected. (FRR) Threshold=0 means that the attempts whose matching score <0 will be rejected; (nobody will be rejected) Threshold=∞ means that the attempts whose matching score < ∞ will be rejected (everybody will be rejected)

31. True Rejection Rate • A impostor is rejected. (TRR) Threshold=0 means that the attempts whose matching score <0 will be rejected; (nobody will be rejected) Threshold=∞ means that the attempts whose matching score < ∞ will be rejected (everybody will be rejected)

32. False Acceptance Rate • A impostor is accepted. (FAR) Threshold=0 means that the attempts whose matching score >0 will be accepted; (everybody will be accepted) Threshold=∞ means that the attempts whose matching score > ∞ will be accepted (nobody will be accepted)

33. 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

34. ROC(2) • Find the optimal point (threshold)

35. 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)

37. 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

38. A A sin(x) 3 sin(x) B + 1 sin(3x) A+B + 0.8 sin(5x) C A+B+C + 0.4 sin(7x) D A+B+C+D A sum of sines and cosines =

39. 5. In Daugman’s approach iris is regarded as a circular pattern (P8: 32-36). In fact we can also take the iris as other pattern, as shown in P8: 29. Please try to design the corresponding scheme.