Associate Professor
University of Twente __ The Netherlands
Luuk Spreeuwers studied Electrical Engineering at the University of Twente, Netherlands, where he earned his PhD in 1992 with a thesis titled Image Filtering with Neural Networks: Applications and Performance Evaluation.
Subsequently Luuk worked at the International Institute for Aerospace and Earth Sciences (ITC) in Enschede, Netherlands; at the University of Twente in a SION project on 3-D image analysis of aerial image sequences; and at the Hungarian Academy of Sciences in Budapest, Hungary in a 3-D textures ERCIM project.
From 1999 to 2005, Luuk worked on 3-D modeling and segmentation of the human heart in MRI at the Image Sciences Institute of the University Medical Centre in Utrecht, the Netherlands. He is currently Associate Professor in the Data Management & Biometrics (DMB) group at the University of Twente and involved in projects on 2D/3D face recognition, face morphing, and finger vein biometrics, among others.
Luuk has published over 80 papers at international conferences and in journals. His expertise spans digital image processing and analysis, medical image analysis, biometrics, and pattern recognition in general.
Can face morphs be detected using face recognition systems?
When the first face morphs were published, it was shown that some commercial face recognition systems generated comparison scores for a morphing attack that were comparable to genuine face comparisons. This means that morphing attacks cannot be distinguished from genuine comparisons. Our recent research shows that other face recognition systems behave differently and generate scores for morphing attacks that lie between genuine and imposter comparisons. In this presentation we explore various ways to make use of these properties in order to make standard face recognition methods more resistant against morphing attacks.
