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An automated handwritten signature verification system is being tested. Twenty five volunteers ('01' to '25') are enrolled for this exercise. They attempt to access the system both as genuine users as well as impostors (i.e., pretending to be someone else). Table 1 shows the data log of the matching scores from these trial attempts (denoting the similarity of the presented biometric to the enrolled template). The scores ranged between [0 1]. A high score implies better match between the live sample and the stored template. Any match score greater than the operator-selected threshold (0) results in successful authentication. (a) Calculate the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of the system for a threshold of 0 = 0.65. (b) Also determine the FAR and FRR values for 0 = 0.25, 0.35, 0.45, 0.55 and 0.75. (c) Hence plot the Detector-Error-Trade-off (DET) characteristics of the system. [You must use a proper graph paper (with appropriate/adequate grids) for this plot. The plot may be hand drawn or software generated.] (d) Determine, graphically or otherwise, the Equal Error Rate (EER) of the system.

An automated handwritten signature verification system is being tested. Twenty five volunteers ('01' to '25') are enrolled for this exercise. They attempt to access the system both as genuine users as well as impostors (i.e., pretending to be someone else). Table 1 shows the data log of the matching scores from these trial attempts (denoting the similarity of the presented biometric to the enrolled template). The scores ranged between [0 1]. A high score implies better match between the live sample and the stored template. Any match score greater than the operator-selected threshold (0) results in successful authentication. (a) Calculate the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of the system for a threshold of 0 = 0.65. (b) Also determine the FAR and FRR values for 0 = 0.25, 0.35, 0.45, 0.55 and 0.75. (c) Hence plot the Detector-Error-Trade-off (DET) characteristics of the system. [You must use a proper graph paper (with appropriate/adequate grids) for this plot. The plot may be hand drawn or software generated.] (d) Determine, graphically or otherwise, the Equal Error Rate (EER) of the system.

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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3. An automated handwritten signature verification system is being tested. Twenty five volunteers ('01' to '25') are enrolled for this exercise. They attempt to access the system both as genuine users as well as impostors (i.e., pretending to be someone else). Table 1 shows the data log of the matching scores from these trial attempts (denoting the similarity of the presented biometric to the enrolled template). The scores ranged between [0 1]. A high score implies better match between the live sample and the stored template. Any match score greater than the operator-selected threshold (0) results in successful authentication. (a) Calculate the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of the system for a threshold of 0 = 0.65. (b) Also determine the FAR and FRR values for 0 = 0.25, 0.35, 0.45, 0.55 and 0.75. (c) Hence plot the Detector-Error-Trade-off (DET) characteristics of the system. [You must use a proper graph paper (with appropriate/adequate grids) for this plot. The plot may be hand drawn or software generated.] (d) Determine, graphically or otherwise, the Equal Error Rate (EER) of the system.
Transcribed Image Text:3. An automated handwritten signature verification system is being tested. Twenty five volunteers ('01' to '25') are enrolled for this exercise. They attempt to access the system both as genuine users as well as impostors (i.e., pretending to be someone else). Table 1 shows the data log of the matching scores from these trial attempts (denoting the similarity of the presented biometric to the enrolled template). The scores ranged between [0 1]. A high score implies better match between the live sample and the stored template. Any match score greater than the operator-selected threshold (0) results in successful authentication. (a) Calculate the False Acceptance Rate (FAR) and the False Rejection Rate (FRR) of the system for a threshold of 0 = 0.65. (b) Also determine the FAR and FRR values for 0 = 0.25, 0.35, 0.45, 0.55 and 0.75. (c) Hence plot the Detector-Error-Trade-off (DET) characteristics of the system. [You must use a proper graph paper (with appropriate/adequate grids) for this plot. The plot may be hand drawn or software generated.] (d) Determine, graphically or otherwise, the Equal Error Rate (EER) of the system.
true ID 01 01 01 01 01 01 02 02 02 02 03 03 03 03 04 04 04 04 04 04 04 04 04 05 05 05 05 05 05 06 06 06 06 06 06 07 07 07 07 07 07 07 08 08 08 claimed ID 01 01 11 17 | 20 22 02 06 13 23 03 03 18 22 04 04 04 04 04 11 13 13 14 05 05 05 05 07 24 06 06 06 06 20 24 07 07 07 07 07 14 18 04 04 08 score 0.98 0.73 0.32 0.21 0.36 0.23 0.43 0.23 0.39 0.27 0.79 0.41 0.16 0.58 0.69 0.61 0.70 0.48 0.64 0.55 0.67 0.90 0.47 0.92 0.68 0.42 0.61 0.25 0.33 0.71 0.78 0.89 0.88 0.17 0.61 0.64 0.67 0.56 0.81 0.96 0.29 0.49 0.57 0.06 0.77 true ID 08 08 10 10 10 10 10 10 11 11 11 11 ~~~~~ 11 12 12 12 12 12 12 12 12 13 13 13 13 13 13 13 14 14 14 14 14 15 15 Table 1 15 15 15 15 15 15 16 16 16 16 claimed ID 13 14 05 |비의의의의 07 10 10 10 19 09 11 11 11 14 01 12 12 12 12 12 20 20 05 13 13 13 13 13 13 04 14 14 14 14 03 10 15 15 15 18 21 25 11 16 16 19 score 0.01 0.41 0.25 0.14 0.64 0.70 0.63 0.47 0.40 0.78 0.95 0.60 0.36 0.39 0.81 0.65 0.95 0.74 0.48 0.56 0.60 0.11 0.72 0.74 0.81 0.63 0.56 0.91 0.11 0.70 0.59 0.29 0.51 0.24 0.32 0.64 0.52 0.73 0.52 0.32 0.46 0.42 0.71 0.95 0.23 true ID 17 17 17 17 17 17 17 18 18 18 19 19 19 20 20 20 21 21 21 21 21 21 22 22 22 22 23 23 23 23 23 23 23 23 24 24 24 25 25 25 25 25 25 25 14 25 claimed ID 08 11 17 17 17 17 21 15 18 18 01 07 12 20 20 20 13 14 19 21 21 25 01 03 12 22 06 08 13 23 23 23 23 23 02 23 24 03 21 24 25 25 25 25 25 score 0.68 0.22 0.80 0.88 0.97 0.69 0.38 0.44 0.56 0.47 0.34 0.08 0.20 0.89 0.77 0.76 0.15 0.43 0.34 0.79 0.72 0.13 0.51 0.72 0.04 0.78 0.26 0.27 0.70 0.92 0.65 0.40 0.18 0.66 0.55 0.68 0.51 0.68 0.21 0.16 0.69 0.77 0.72 0.97 0.71
Transcribed Image Text:true ID 01 01 01 01 01 01 02 02 02 02 03 03 03 03 04 04 04 04 04 04 04 04 04 05 05 05 05 05 05 06 06 06 06 06 06 07 07 07 07 07 07 07 08 08 08 claimed ID 01 01 11 17 | 20 22 02 06 13 23 03 03 18 22 04 04 04 04 04 11 13 13 14 05 05 05 05 07 24 06 06 06 06 20 24 07 07 07 07 07 14 18 04 04 08 score 0.98 0.73 0.32 0.21 0.36 0.23 0.43 0.23 0.39 0.27 0.79 0.41 0.16 0.58 0.69 0.61 0.70 0.48 0.64 0.55 0.67 0.90 0.47 0.92 0.68 0.42 0.61 0.25 0.33 0.71 0.78 0.89 0.88 0.17 0.61 0.64 0.67 0.56 0.81 0.96 0.29 0.49 0.57 0.06 0.77 true ID 08 08 10 10 10 10 10 10 11 11 11 11 ~~~~~ 11 12 12 12 12 12 12 12 12 13 13 13 13 13 13 13 14 14 14 14 14 15 15 Table 1 15 15 15 15 15 15 16 16 16 16 claimed ID 13 14 05 |비의의의의 07 10 10 10 19 09 11 11 11 14 01 12 12 12 12 12 20 20 05 13 13 13 13 13 13 04 14 14 14 14 03 10 15 15 15 18 21 25 11 16 16 19 score 0.01 0.41 0.25 0.14 0.64 0.70 0.63 0.47 0.40 0.78 0.95 0.60 0.36 0.39 0.81 0.65 0.95 0.74 0.48 0.56 0.60 0.11 0.72 0.74 0.81 0.63 0.56 0.91 0.11 0.70 0.59 0.29 0.51 0.24 0.32 0.64 0.52 0.73 0.52 0.32 0.46 0.42 0.71 0.95 0.23 true ID 17 17 17 17 17 17 17 18 18 18 19 19 19 20 20 20 21 21 21 21 21 21 22 22 22 22 23 23 23 23 23 23 23 23 24 24 24 25 25 25 25 25 25 25 14 25 claimed ID 08 11 17 17 17 17 21 15 18 18 01 07 12 20 20 20 13 14 19 21 21 25 01 03 12 22 06 08 13 23 23 23 23 23 02 23 24 03 21 24 25 25 25 25 25 score 0.68 0.22 0.80 0.88 0.97 0.69 0.38 0.44 0.56 0.47 0.34 0.08 0.20 0.89 0.77 0.76 0.15 0.43 0.34 0.79 0.72 0.13 0.51 0.72 0.04 0.78 0.26 0.27 0.70 0.92 0.65 0.40 0.18 0.66 0.55 0.68 0.51 0.68 0.21 0.16 0.69 0.77 0.72 0.97 0.71
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