On Face Image Quality Measures

The classification reliability is an essential problem in biometric verification systems. In the presence of a possible mismatch between system’s training and testing conditions, a measure of that mismatch is necessary in order to estimate the degree of trust one can have in the classification decisions. In the case of face verification from plain images, there are many factors that can affect the image quality, and thus create a condition mismatch. In this paper we identify the most commonly encountered causes of face image degradation due to the recording conditions, and propose corresponding quality measure methods. We show on publicly available databases that proposed methods can be effectively used to estimate the verification reliability using a probabilistic framework.