PRNU-based detection of morphed face images

Abstract

In the recent past, face recognition systems have been found to be highly vulnerable to attacks based on morphed biometric samples. Such attacks pose a severe security threat to biometric recognition systems across various applications. Apart from some algorithms, which have been reported to reveal practical detection performance on small in-house datasets, approaches to effectively detect morphed face images of high quality have remained elusive. In this paper, we propose a morph detection algorithm based on an analysis of photo response non-uniformity (PRNU). It is based on a spectral analysis of the variations within the PRNU caused by the morphing process. On a comprehensive database of 961 bona fide and 2,414 morphed face images practical performance in terms of detection equal error rate (D-EER) is achieved. Additionally, the robustness of the proposed morph detection algorithm towards different post-processing procedures, e.g. histogram equalization or sharpening, is assessed.