Image-based attributes of multi-modality image quality for contactless biometric samples
Résumé
The quality of a biometric sample is one of
the main criteria having a direct influence on the overall
performance of a biometric system. There are many existing
researches focusing on biometric sample quality assessment,
but different evaluation approaches measure different quality
attributes and most of them focus on measuring modalitybased
attributes. Meanwhile, different biometric modalities
seem to be isolated from each other in the image quality
evaluation process. Quality metrics that can evaluate multimodality
biometric sample quality is rarely considered. The
link of sample quality evaluation between different modalities
can be established by using image-based quality metrics, which
are able to assess image-based quality attributes. This could
be the solution of developing multi-modality biometric sample
quality evaluation approaches especially when the fingerprint
acquisition sensor becomes contactless. In order to investigate
the common framework of biometric sample quality assessment
between contactless fingerprint, face, and iris, we will first
review the commonly used image-based quality attributes for
three modalities by surveying existing literature. Based on the
survey, we identify and categorize these attributes to propose a
refined selection of important ones for the assessment of multimodality
biometric sample quality.