Morphing Attack Detection using Laplace operator based features
The vulnerability of facial recognition systems through morphing attacks is a known problem. Since the first publication about this vulnerability of facial recognition systems, a variety of morphing attack detection methods have been presented, promising an automated detection of such fraudulent attacks. In this work, a new approach is presented attempting to distinguish bona fide from morphed images based on information about the edges in the image extracted by the Laplace operator. It can be demonstrated that the features employed contain information that can contribute to the detection of morphed face images.