Image-based attributes of multi-modality image quality for contactless biometric samples

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 modality-based attributes. Meanwhile, different biometric modalities seem to be isolated from each other in the image quality evaluation process. Quality metrics that can evaluate multi-modality 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 multi-modality biometric sample quality.