PD ISO/IEC TR 29198:2013
Information technology. Biometrics. Characterization and measurement of difficulty for fingerprint databases for technology evaluation
Standard number: | PD ISO/IEC TR 29198:2013 |
Pages: | 40 |
Released: | 2013-12-31 |
ISBN: | 978 0 580 68454 8 |
Status: | Standard |
PD ISO/IEC TR 29198:2013
This standard PD ISO/IEC TR 29198:2013 Information technology. Biometrics. Characterization and measurement of difficulty for fingerprint databases for technology evaluation is classified in these ICS categories:
- 35.240.15 Identification cards and related devices
This Technical Report provides guidance on estimating how “challenging“ or “stressing“ 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 aformentioned 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.