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How does one determine the “Receiver Operating Characteristic” (ROC) of a biometric system?

biometric determine ROC
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How does one determine the “Receiver Operating Characteristic” (ROC) of a biometric system?

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The FAR/FRR curve pair is excellently suited to set an optimal threshold for the biometric system. Further predictors of a system’s performance, however, are limited. This is partially due to the interpretation of the threshold and similarity measures. The definition of the similarity measures is a question of implementation. Almost arbitrary scaling and transformations are possible, which affect the appearance of FAR/FRR curves but not the FAR-FRR values at a certain threshold. A popular example is the use of a “distance measure” between the biometric reference and the scanned biometric features. The greater the similarity, the smaller the distance. The result is a mirror image of the FAR/FRR curves. A favorite trick is to stretch the scale of FAR/FRR curves near the EER (Equal Error Rate: FAR(th) = FRR(th)), (i.e., using more threshold values) thus making the system appear less sensitive to threshold changes. In order to reach an effective comparison of different systems, a descripti

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A biometric system test usually starts by determining the similarities of different biometric features and a saved reference feature. After many measurements, one receives a histogram or distribution for authorized users and another for unauthorized users showing the frequency of matches per similarity rating. In an ideal case, the two distribution graphs should overlap as little as possible. When setting a certain similarity rating as a threshold for determination of authorized versus non authorized users, the false acceptance rate (FAR) is the number of non authorized users whose similarity rating happens to fall above the threshold compared to all attempts. On the other hand, a false rejection rate (FRR) is the number of authorized users whose similarity ratings happen to fall below this threshold compared to all attempts. Through integration (in practice, successive summation) of these distribution graphs, FAR and FRR graphs are determined, which are dependent on the adjustable ado

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