BSI PD ISO/IEC TR 29198:2013

Current Revision
Information technology. Biometrics. Characterization and measurement of difficulty for fingerprint databases for technology evaluation

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BSI PD ISO/IEC TR 29198:2013

Information technology. Biometrics. Characterization and measurement of difficulty for fingerprint databases for technology evaluation

PUBLISH DATE 2013
PAGES 40
BSI PD ISO/IEC TR 29198:2013

This Technical Report provides guidance on estimating how β€œchallengingβ€œ or β€œstressingβ€œ is an evaluation dataset for fingerprint recognition, based on relative sample quality, relative rotation, deformation, and overlap between impressions.

In addition, this Technical Report establishes a method for construction of datasets of different levels of difficulty. This Technical Report defines the relative level of difficulty of a fingerprint dataset used in technology evaluation of fingerprint recognition algorithms. Level of difficulty is based on differences between reference and probe samples in the aforementioned factors.

This Technical Report addresses such issues as:

  • characterizing level of difficulty attributable to differences between samples acquired from the same finger,

  • developing statistical methodologies for representing the level of difficulty of a fingerprint dataset by aggregating influencing factors,

  • comparing the level of difficulty of different fingerprint datasets,

  • defining procedures for testing and reporting the level of difficulty of fingerprint datasets collected for technology evaluation,

  • analysing mated pair data characteristics based on comparison scores,

  • describing the archived data selection methodology for building a dataset for evaluation.

This Technical Report provides guidelines for comparing the relative level of difficulty of fingerprint datasets.

Outside the scope of this Technical Report are:

  • defining the quality of individual fingerprint images,

  • defining the methodologies or explicit measures for evaluating or predicting the performance of fingerprint recognition algorithms.

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