Quality metrics influence on iris recognition systems performance

Abstract

When working with biometrics, regardless of the modality, it is essential to consider data quality, as it can limit the accuracy of recognition systems. In this context, the assessment of biometric samples quality by defining quality metrics can be used to enhance the performance and functionality of a biometric system. In this work, the influence of ISO/IEC 29794-6 quality metrics on iris recognition systems performance has been analysed. To carry out the analysis, the corresponding metrics have been calculated according to the computational method detailed in the standard and a quality score has been obtained. Then, in order to determine the metrics influence, an open source iris recognition system as well as one publicly available dataset, have been used.Results show to what extent an iris recognition system can be affected by input images quality, and also the most influential quality metrics on recognition accuracy.

OSIRIS: An open source iris recognition software

“…OSIRIS Reference System has been cited in several papers since 2009, in different topics such as iris segmentation (23), (24), (25), (26), (27), and (28), iris aging (29), cryptography (30), (31), and (32) and quality assessment (33). To our knowledge, OSIRISV2 and OSIRISV4.1 14 11 have been respectively used in 14 and 11 works as reported in Table 1.…”