IMIS | Expertplatform - Waterbouwkundig Laboratorium

The Signal and Image Centre (SIC) is a research group part of the Electrical Engineering Department of the Faculty of Applied Sciences of the Royal Military Academy.

The SIC expertise includes restoration and compression, pattern recognition, remote sensing, data fusion and robotics. The strong interaction between those fields of activities and the concerned experts is one originality of the Centre.

In image compression, the SIC is developing for the European Space Agency (ESA) and for EUMETSAT lossy and lossless compression methods based on the wavelet transform and on the JPEG standard.

In image restoration, the SIC develops adaptive methods based on the processing of local description of the information.

In pattern recognition, the SIC is specialized in surveillance systems and has developed dedicated software for object, target and face recognition. Specifically, methods have been developed for face recognition (ACTS project M2VTS) and for the recognition of structured objects in a complex environment (EUCLID RTP6.2).

In remote sensing, the SIC is mainly using its know-how in feature extraction for developing new processing methods. In this respect, the laboratory is involved in several European and national projects. It is active in the automatic georeferencing of multi-spectral satellite images (EUCLID RTP9.4). In this context, the extraction and the matching of characteristics are performed automatically on multi-spectral satellite images (namely SPOT and ERS1 images). The SIC also develops tools and methods intended for the semi-automatic interpretation of multi-spectral high resolution satellite images in benefit of the Western European Union (WEU) (data fusion).
The SICis active in the development of methods on the slant to ground range conversion of SAR interferometric phase-unwrapped satellite images (TELSAT III in collaboration with the Centre Spatial de Liège).
The SIC is participating actively in a project analyzing the possibility to classify the different types of vegetation by means of SAR images (ESPRIT Nr 21042 CTIAC).

In speech the SIC is specialized in person authentication and has developed and implemented some speaker recognition algorithms. Activities on multi-modal fusion have been undertaken, focusing on the verification of a person's identity, in the scope of the M2VTS ACTS project.

In robotics, the SIC applies pattern recognition methods for robot vision and autonomous vehicles. In this respect, the SIC leads a research project relative to the humanitarian mine clearance in collaboration with other Belgian universities, namely the ULB, RUG and the VUB. The robotics unit is also involved in the European project CLAWAR on "CLimbing And WAlking Robots".

The SIC also organizes training in the domains wherein it is skilled, especially in data fusion, and is open to collaboration in common research projects with other universities over the world and in supporting PhD theses. Foreign researchers and students are welcome.

Publications (10)

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( 5 peer reviewed )

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Tellez, O.L. (2018). Human-in-the-loop for autonomous underwater threat recognition, in: OCEANS 2018 MTS/IEEE Charleston. Oceans (New York), : pp. 5. https://dx.doi.org/10.1109/OCEANS.2018.8604559, more
Borghys, D.; Perneel, C.; Bouaraba, A. (2012). Activity monitoring in a commercial harbor using multitemporal repeat-pass interferometric SAR data, in: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2012). Proceedings of a meeting held 22-27 July 2012, Munich, Germany. IEEE International Symposium on Geoscience and Remote Sensing IGARSS, : pp. 7440-7443. http://dx.doi.org/10.1109/IGARSS.2012.6351941, more
Borghgraef, A.; Barnich, O.; Lapierre, F.; Van Droogenbroeck, M.; Philips, W.; Acheroy, M. (2010). An evaluation of pixel-based methods for the detection of floating objects on the sea surface. Eurasip Journal on Advances in Signal Processing 2010: 978451. https://dx.doi.org/10.1155/2010/978451, more
Closson, D.; Abou Karaki, N.; Milisavljevic, N.; Hallot, F.; Acheroy, M. (2010). Salt-dissolution-induced subsidence in the Dead Sea area detected by applying interferometric techniques to ALOS Palsar Synthetic Aperture Radar images. Geodin. Acta 23(1-3): 65-78. https://dx.doi.org/10.3166/ga.23.65-78, more
Lapierre, F.D.; Borghgraef, A.; Vandewal, M. (2010). Statistical real-time model for performance prediction of ship detection from microsatellite electro-optical imagers. Eurasip Journal on Advances in Signal Processing 2010: 475948. https://dx.doi.org/10.1155/2010/475948, more
Tellez, O.L. (2019). Underwater threat recognition: Are automatic target classification algorithms going to replace expert human operators in the near future?, in: OCEANS 2019 - Marseille. pp. 4. https://hdl.handle.net/10.1109/OCEANSE.2019.8867168, more
Tellez, O.L.; Papili, S. (2017). Sea-floor characterization related to object-detection performance of sonar systems: a case study, in: OCEANS 2017 - Aberdeen. pp. 4. https://dx.doi.org/10.1109/OCEANSE.2017.8084804, more
Lopera, O.; Papili, S. (2016). New methodology for modern monitoring, in: Degraer, S. et al. (Ed.) North Sea Open Science Conference 7-10/11/2016. Abstract Booklet. pp. 101, more
Papili, S.; Lopera, O. (2016). High frequency response on seafloor signature: structure for an innovative methodology for modern monitoring, in: Degraer, S. et al. (Ed.) North Sea Open Science Conference 7-10/11/2016. Abstract Booklet. pp. 78, more
Tellez, O.L.; Papili, S. (2016). An introductory study of the impact of environmental parameters in the performances of imaging sonar systems, in: MTS/IEEE Oceans 2016 Conference. pp. 6, more

Projects (2)	Top \| Persons \| Publications
ASME: Airborne sensor system for the protection of the marine environnement, more TIRIS: Measuring chemical pollutant gases in the port of Antwerp using imaging spectroscopy, more

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