Dr. Luuk Spreeuwers studied Electrical Engineering at the University of Twente, Netherlands. In 1992 he obtained his PhD from the University of Twente. The title of his PhD-thesis is: Image Filtering with Neural Networks: Applications and Performance Evaluation. Subsequently Luuk Spreeuwers worked at the International Institute for Aerospace and Earth Sciences (ITC) in Enschede, Netherlands, the University of Twente in a SION project on 3-D image analysis of aerial image sequences and in Budapest at the Hungarian Academy of Sciences in a 3-D textures ERCIM project. From 1999-2005 Luuk Spreeuwers worked on 3-D modelling and segmentation of the human heart in MRI at the Image Sciences Institute of the University Medical Centre in Utrecht, the Netherlands. Currently, he is an Associate Professor at the Data Management and Biometrics Group of the Department of EEMCS of the University of Twente, Netherlands where he is the leader of the biometrics sub-group. In addition, he is the programme mentor of the Computer Vision and Biometrics Master Specialisation and is actively involved in teaching Bachelor's and Master's courses and president of the EE Programme Committee. He was nominated 6 times for the EE Educational award and won the prize in 2018. Luuk Spreeuwers has published over 100 papers in international conferences and journals. In 2015 he published a paper on 3D face recognition where he claimed the world's best performance on a recognised benchmark in 3D face recognition. In 2017 he won the best paper award at the BIOSIG conference with the paper titled: "De-Duplication using automated Face Recognition. An accurate mathematical Model and all Babies are equally cute". He was and is involved in numerous national and European projects among which 3DFace, SOTAMD and currently iMARS. His expertise involves digital image processing and analysis, medical image analysis, biometrics and pattern recognition in general.

Expertise

  • Computer Science

    • Face Recognition
    • Biometrics
    • Morphing
    • Recognition System
    • Forensics
    • Attack
    • Database
    • Detection

Organisations

Publications

2024

Analysing the robustness of finger vein recognition: cross-dataset reliability and vein utility (2024)Eurasip Journal on Image and Video Processing, 2024. Article 35. Arican, T., Veldhuis, R. & Spreeuwers, L.https://doi.org/10.1186/s13640-024-00643-2A Survey on Automatic Face Recognition Using Side-View Face Images (2024)IET biometrics, 2024(1). Article 7886911. Santemiz, P., Spreeuwers, L. J. & Veldhuis, R. N. J.https://doi.org/10.1049/2024/7886911Understanding the imaging process and role of illumination in finger vascular pattern recognition (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Normakristagaluh, P.https://doi.org/10.3990/1.97890365618393D Printed Realistic Finger Vein Phantoms (2024)In 2024 12th International Workshop on Biometrics and Forensics, IWBF 2024. IEEE. Spreeuwers, L., van der Grift, R. & Normakristagaluh, P.https://doi.org/10.1109/IWBF62628.2024.10593906Improving Fully Automated Landmark-based Face Morphing (2024)In 2024 12th International Workshop on Biometrics and Forensics, IWBF 2024. IEEE. Batskos, I. & Spreeuwers, L.https://doi.org/10.1109/IWBF62628.2024.10593985Patch-based Finger Vein Verification using Convolutional Variational Autoencoder (2024)In 2024 12th International Workshop on Biometrics and Forensics, IWBF 2024. IEEE. Ismayilov, R., Arican, T., Spreeuwers, L. & Zeinstra, C.https://doi.org/10.1109/IWBF62628.2024.10593973The Role of Facial Hair on Roman Emperors' Face Recognition (2024)In 2024 12th International Workshop on Biometrics and Forensics, IWBF 2024. IEEE. Lestriandoko, N. H., De Wit, F., Betjes, S., Heijnen, S., Hekster, O. & Spreeuwers, L.https://doi.org/10.1109/IWBF62628.2024.10593824Vulnerability of face recognition to morphing: a latent space perspective (2024)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Kelly, Ú. M.https://doi.org/10.3990/1.9789036561396A Comparative Study of Cross-Device Finger Vein Recognition Using Classical and Deep Learning Approaches (2024)IET biometrics, 2024. Article 3236602. Arıcan, T., Veldhuis, R., Spreeuwers, L., Bergeron, L., Busch, C., Jalilian, E., Kauba, C., Kirchgasser, S., Marcel, S., Prommegger, B., Raja, K., Ramachandra, R. & Uhl, A.https://doi.org/10.1049/2024/3236602Language-Based Augmentation to Address Shortcut Learning in Object-Goal Navigation (2024)In Proceedings - 2023 7th IEEE International Conference on Robotic Computing, IRC 2023 (pp. 1-8). IEEE. Hoftijzer, D., Burghouts, G. & Spreeuwers, L.https://doi.org/10.1109/IRC59093.2023.00007

Research profiles

Courses academic year 2024/2025

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2023/2024

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