How is the probability distribution function measured for a biometric systems authorized and unauthorized users?
In order to investigate the performance of a biometric verification system, one looks at how the system reacts to a large number of inquires for biometric features from authorized as well as unauthorized users. Due to natural fluctuations and measurement imperfections, the results of such an investigation are never absolutely certain, instead are only predictable to a certain extent. In order to determine the error rates, “false acceptance” and “false rejection,” the yes/no decisions of “authorized/unauthorized” are not used, instead the underlying degree of similarity between an inquiry and the saved reference feature. In a series of measurements, similarity ratings (“score values”) are collected for authorized and unauthorized users. Then the frequency of incidence is counted for every similarity rating. After being normalized with the total number of inquiries, both resulting histograms make up an approximation to the probability distribution function. They show the measured estimat
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