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Analysis of Minutiae Quality for Improved Workload Reduction in Fingerprint Identification
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Datum
2022
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Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
The workload of biometric identification in large fingerprint databases poses a challenging
problem. Efficient schemes for biometric workload reduction are a topic of ongoing research.
Some of the state-of-the art approaches rely on triangles of minutia points generated by Delaunay
triangulation, which are then used for indexing. In this paper, we investigate how quality estimation
at the minutia level can improve the performance of such algorithms and hence the system workload.
In order to reduce the number of spurious and missing minutiae, we analyse the impact of selecting
minutiae points based on their qualities. This, in turn, can significantly distort the triangulation. In
addition, we consider the usefulness of the average minutia quality as an additional criteria of the
minutia triangles for indexing. Our results show that both strategies lead to a significant reduction
in biometric workload compared to a baseline solution (i.e. exhaustive search) – down to 36% on
average.