Impact of out-of-focus blur on face recognition performance based on modular transfer function

Abstract

It is well recognized that face recognition performance is impacted by the image quality. As face recognition is increasingly used in semi-cooperative or unconstrained applications, quantifying the impact of degraded image quality can provide the basis for improving recognition performance. This study uses a range of real out-of-focus blur obtained by controlled changes of the focal plane across face video sequences during acquisition from the Q-FIRE dataset. The modulation transfer function (MTF) method for measuring sharpness is presented and compared with other sharpness measurements with a reference of the co-located optical chart. Face recognition performance is then examined at eleven sharpness levels based on the MTF quality metrics. Experimental results show the MTF quality metrics better quantify a range of blur compared to the optical chart and offer a useful range of interest for face recognition performance. This paper demonstrates the applicability of an image blur quality metric as auxiliary information to supplement face recognition systems through the analysis of a unique database.