P329 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group

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Konferenzbeitrag
Utility-based performance evaluation of biometric sample quality assessment algorithms
(BIOSIG 2022, 2022) Olaf Henniger, Biying Fu and Cong Chen
The quality score of a biometric sample is expected to predict the sample’s utility, but a universally valid definition of utility is missing. A harmonized definition of utility would be useful to facilitate the comparison of biometric sample quality assessment algorithms. This paper generalizes the utility of a biometric sample as normalized difference between the means of non-mated and mated comparison scores with respect to this sample. Using a face image data set, we show that discarding samples with low utility scores determined in this way results in a rapidly declining false non-match rate. The obtained utility scores can be used as ground-truth utility labels for training biometric sample quality assessment algorithms and for summarizing their prediction performance in a single plot and in a single figure of merit based on the proposed utility score definition.