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Image Processing

Members

Activities

The aim of the Image Processing Research Unit is to develop tools and methods for solving real world problems involving images. The team gained its experience from various national and international projects mainly in Remote Sensing (RTP9.4, SAHARA, ARMURS) and in Image Processing for Humanitarian Demining (Hudem) and more generally for security (GMOSS) applications. Today the concerned applications include cartography, graphics vectorisation and seamine detection.

In cartography, the current focus is on stereo and multi-stereo processing. The digital surface and digital terrain models (DTM and DSM) are computed from airborne images. Computed heights combined with radiometry and compared with an object database provide change information which can be exploited by a cartographic agency. Special interest is devoted to buildings and roads.

Graphics vectorisation aims at transforming a raster into vectors representing the objects present on the graphics.Low-level image processing tools such as colour palette extraction, line and edge extraction, and textured areas extraction are developed and applied to scanned map vectorisation.

Seamine detection is performed on high resolution images collected using synthetic aperture sonars. Image segmentation and shape recognition algorithms are currently applied to characterize the acoustic mine signature (shadow and echo) in order to detect and classify seamines.

Research projects

DAP-16-9

The Confident project, conducted in the Improvised Explosive Devices Detection programm of the European Defence Agency, consists in providing IED early warning for convoys.

The Royal Military Academy is in charge of the processing and data fusion of the infrared images with the image coming from the other detectors.

DAP-16-8

The aim of the study is to develop (semi-)automatic image analysis methods in order to help vectorize topo-geographic objects from satellite imagery and to integrate these in the Geographic service of the Defense in charge of the MGCP project.

EO Regions

EO Regions aims at optimizing earth observeration services and valorizing scientific know-how from universities and the private sector by offering substantial and competitive services and by mobilizing users through the demonstration of the potential of these services.

The activities of RMA consist in analyzing and developping change-detection algorithms on stacks of Sentinel-1 images.

SPaceborne Radar INterferometric Techniques for Humanitarian Demining Land Release (SPRINT)

Development of Earth observation SAR-based tools to improve surveys required for humanitarian demining. Analysis and modelling of long term mechanisms and processes related to potential indicators of contaminated areas through exploitation of time series of ERS and ENVISAT archives will be performed and validated in Croatia. The idea is to differentiate human-induced effects from natural ones by exploiting the combination of the amplitude and phase changes of the signal. The same tools could be used for food security applications. The project could serve as a feasibility study for using stacks of free Sentinel-1 images.

SIC/05

The study aims first at automatically extract Digital Surface Models using very high spatial and radiometric resolution images and multiview modes. Second, these DSM will be exploited to perform change detection and produce landscape models.

Vehicle speed measurement using time lapse cameras

The aim of this project is to develop, test and validate a library allowing to determine the speed of cars passing by from time-lapse images.

SUM (Surveillance in an Urban environment using Mobile sensors)

The aim of this project is to develop a low-cost multi-sensor vehicle protection system using a data fusion engine in order to enhance situational awareness and aid command and control for a moving vehicle in an urban environment, as well as to protect critical static points such as road blocks or outposts, taking into account the operational needs defined by end-users. The system will be able to detect potential threats at large distances while driving at a normal cruising speed. Furthermore, the system will be able to recognize and characterize threats in more detail at smaller distances and at slower speeds. Based on the working conditions and the operator\'s instructions, the system will be able to switch between operating modes for the overall system and for the individual sensors (spot mode, scanning mode etc.)

MRN09

This project addresses the limitations for observation, detection and classification of seabed ground targets, in particular mines. It will target the aspect of high-resolution synthetic-aperture sonar image by investigating the use of interferometric SAS methods (in particular single- and dual-pass interferometry), in order to facilitate the classification task. In the same philosophy as dual-pass interferometry, a new concept of imaging technique based on planar synthetic aperture sonar (P-SAS) will be investigated, which takes advantage of the overlap of both ping-to-ping and track-to-track footprints to improve the imaging resolution in both along-track and across-track directions.

A second aspect of the study will be the classification by itself; herein the speckle reduction task will be considered as well as the classification based on the three categories mentioned earlier; shadow based characterization, echoes based characterization and fusion based methods.

ARMURS: Automatic Recognition for Map Update by Remote Sensing

Description: Topographical data producers are currently confronted the need of a faster updating method. Although state-of-the-art techniques exist, no automated tool predicts and locates changes.

The general objective of the project is to capitalize partners\' knowledge in the development of a demonstrator to assist data producers in updating more efficiently their topographic database by using state-of-the-art image processing and statistical analysis techniques. Data will include remote sensing images, together with socio-economical data.

To achieve this general objective, two main axes are distinguished:

- At a regional scale, the objective is to analyze topographical dabases from multiple sources such as satellite images, demographic database, or economic database in order to predict information about the localization of changes in man-made structures (such as houses, roads, etc.).

- At a local scale, for areas of predicted changes the older databases will be compared w

OCTOPUS

The method developed for NGI by SIC in the scope of the ETATS project (STEREO SR/00/21) to detect changes in buildings and roadnetwork from SPOT5 images and the Top10v-GIS topographic data base (conceptually at 1:10 000) of NGI, has produced good results on a set of zones, but could not be validated sufficiently in the foreseen time frame during the ETATS project. Moreover, taking into account the tests realized and in order to make the application more flexible, NGI prefers a modular version of the realized software under the form of successions of scripts instead of a global graphical interface. Finally, the NGI wish that the method could accept as input other types of images than SPOT5 images, as aerial photos, orthophotos and mosaics.

At the end of this project, the NGI will have a versatile and adapted prototype to help the updating of topogeographical data.

Adaptation du Système d Information Géographique PARADIS développé dans le cadre de l étude C4-01 aux besoins spécifiques de l ONG APOPO.

Les objectifs sont les suivants :

1. Fournir à APOPO un système clé sur porte pour la planification de leurs opérations de déminage;

2. Offrir au système PARADIS une grande visibilité du fait de son intégration au sein des activités d une organisation de déminage reconnue, innovante et hautement médiatisée;

3. Généraliser le système PARADIS afin d élargir le spectre des utilisateurs potentiels.

La méthodologie employée sera conforme à celle utilisée dans le cadre du développement du système PARADIS (étude C4-01). Elle repose sur trois axes principaux:

1. une expérience approfondie des potentialités et des contraintes liées aux SIG;

2. la connaissance des besoins des utilisateurs finaux et des possibilités d intégration de ces besoins dans le système; cette connaissance a été acquise lors de trois tests de faisabilité réalisés sur le terrain en collaboration avec APOPO Mozambique;

3. le développement proprement dit, réalisé en collaboration directe avec APOPO.

GMOSS:

The aim of the GMOSS network of excellence is to integrate Europe?s civil security research so as to acquire and nourish the autonomous knowledge and expertise base Europe needs if it is to develop and maintain an effective capacity for global monitoring using satellite earth observation.

GEMITOR

The objective of the GEMITOR project is to generate a Numerical Surface Model (NSM) with a resolution that is as high as possible. This NSM would then serve as input for the EMSOR project to which the GEMITOR project is linked.

Generating NSM from SAR interferometrie has proved to be challenging at very high resolution. In particular, the phase unwrapping operation has to be re-examined, for instance by adopting a multiresolution approach.

EMSOR “Extraction Automatique de structures humaines à partir d’images à très Haute Résolution Optiques et SAR pour détection de changement”

EMSOR vise 2 applications complémentaires de la détection de structures humaines, à savoir : la mise à jour de données cartographiques en routine et la mise à jour de cartes en temps de crise avec évaluation des dégâts survenus.

EMSOR va intégrer voire développer les méthodes nécessaires à l’analyse des données SAR pour les applications en sécurité (résolution 1m), à l’analyse des données optiques (résolution 1m) et à la fusion de données SAR et optiques.

EMSOR, est intégré dans un réseau destiné à faciliter l’échange d’expertise, de données et la comparaison de résultats.

Etats

The National Geographic Institute (of Belgium) is in charge of the production of the digital topo-geographic data over Belgium at the scale of 1:10000. In order to keep up with the evolution of the situation on the terrain, the NGI has to plan for the update of these data and inform its user about the status of that update. Detection of areas that have undergone a significant evolution with respect to the know situation in the database is thus required.

The role of RMA in this project is to detect those areas. More specifically, the focus will be put on the detection of the communication network (roads, railroad) and the build-up areas. RMA will produce a software prototype that will interface with a Geographical Information System and that will compute a 'change index' for fixed-size cells on a regular grid using very high resolution satellite images.

SMART

The goal of the SMART project is to provide a GIS-based system - the SMART system - augmented with dedicated tools and methods designed to use multispectral and radar data in order to assist the human analyst in the interpretation of the mined scene. The use of SMART includes a short field survey to collect knowledge about the site, a flight campaign to record the data, and the use of the SMART system by an operator to detect indicators of presence or absence of minefields. The operator will prepare thematic maps that will synthesise all the knowledge gathered with these indicators. These maps of indicators can be transformed into ‘danger maps’ showing how dangerous an area may be according to the location of known indicators. These maps are designed to help the area reduction process.
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Publications

  1. C Beumier and M Idrissa. Digital terrain models derived from digital surface model uniform regions in urban areas. International Journal of Remote Sensing, 37(15):3477-3493, 2016.
  2. Mahamadou Idrissa and Charles Beumier. Generic epipolar resampling method for perspective frame camera and linear push-broom sensor. International Journal of Remote Sensing, 37(15):3494-3504, 2016.
  3. Olga Lopera and Sonia Papili. An introductory study of the impact of environmental parameters in the performances of imaging sonar systems. In OCEANS MTS/IEEE Monterey, pages 1-4, Monterey, 2016. IEEE.
  4. Sonia Papili and Olga Lopera. High frequency response on seafloor signature: structure for an innovative methodology for modern monitoring. In S. et al. Degraer, editor, North Sea Open Science Conference, page 78, Oostende, 2016. Royal Belgian Institute of Natural Sciences and Belgian Biodiversity Platform.
  5. C Beumier and M Idrissa. Deriving a DTM from a DSM by Uniform Regions and Context. EARSeL eProceedings, 14(1):16-24, 2015.
  6. Sonia Papili, C Jenkins, Marc Roche, Thomas Wever, Olga Lopera, and Vera Van Lancker. INFLUENCE OF SHELLS AND SHELL DEBRIS ON BACKSCATTER STRENGTH: INVESTIGATION USING MODELING, SONAR MEASUREMENTS AND SAMPLING ON THE BELGIAN CONTINENTAL SHELF. In Blondel et al., editor, Seabed and Sediment Acoustics: Measurements and Modelling, pages 1-7, Bath, 2015. Institute of Acoustics.
  7. Marc Roche, Matthias Baeye, Jeroen De Bisschop, Koen Degrendele, Lis De Mol, Sonia Papili, Olga Lopera, and Vera Van Lancker. BACKSCATTER STABILITY AND INFLUENCE OF WATER COLUMN CONDITIONS: ESTIMATION BY MULTIBEAM ECHOSOUNDER AND REPEATED OCEANOGRAPHIC MEASUREMENTS, BELGIAN PART OF THE NORTH SEA. In Blondel et al., editor, Seabed and Sediment Acoustics: Measurements and Modelling, pages 74-84, Bath, 2015. Institute of Acoustics.
  8. C Beumier and M Idrissa. Building detection with multi-view colour infrared imagery. EARSeL eProceedings, 13(2):77-84, 2014.
  9. Azzedine Bouaraba. Coherent change detection using high-resolution SAR images. PhD thesis, Royal Military Academy & EMP Algeria, 2014.
  10. Olga Lopera and Wei Liu. An Introductory Study for Applying Single-pass Interferometry to Hull Mounted Sonar Data for Target Height Estimation.. In EUSAR 2014, page 4, Berlin, Germany, 2014.
  11. C Beumier and M Idrissa. Extraction de MNS et Application à la Détection de Changement du Bâti. In Traitement et Analyse de l'Information Méthodes et Applications - TAIMA 2013, Hammamet, Tunisia, 2013.
  12. D. Borghys, M. Idrissa, M. Shimoni, O. Friman, M. Axelsson, M. Lundberg, and C. Perneel. Fusion of multispectral and stereo information for unsupervised target detection in very high resolution airborne data. In Proc. SPIE Signal Processing, Sensor Fusion, and Target Recognition XXII, SPIE Vol 8745, Baltimore, April 2013, 2013.
  13. R Heremans and W Mees. Vehicle threat locating via the detection of anomalies on roads and their verges. In Proceedings of the IASTED International Conference on Computer Graphics and Imaging, CGIM 2013, pages 54-61, 2013.
  14. Olga Lopera and Yves Dupont. Interferometric-SAS applied to SHADOWS - A case study. In Oceans 2013, page 4, Bergen, Norway, 2013.
  15. B Mertens, B De Leener, C Beumier, O Debeir, P Lambert, and A Delchambre. Robust Structured Light Pattern for Use witha Spatial Light Modulator in 3D Endoscopy. Int. Journal of Optomechatronics, 7:105-121, 2013.
  16. M. Shimoni, M. Idrissa, D. Borghys, T. Haavardsholm, T-O. Opsahl, and C. Perneel. Urban features classification using 3D hyperspectral data. In 5th IEEE Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Florida, USA, June 2013, 2013.
  17. C Beumier. Speed Estimation Thanks to Two Images from One Stationary Camera. In Iberoamerican Congress on Pattern Recognition - CIARP 2012, Buenos Aires, Argentina, 2012.
  18. C Beumier. Vehicle Speed Estimation from Two Images for LIDAR Second Assessment. In Int. Conf. on Computer Vision Theory and Applications - VISAPP12, Roma,Italy, 2012.
  19. C. Beumier and M. Idrissa. Building Change Detection from Uniform Regions. In beroamerican Congress on Pattern Recognition (CIARP 2012), 2012.
  20. C Beumier and M Idrissa. Building Change Detection from Uniform Regions. In Iberoamerican Congress on Pattern Recognition - CIARP 2012, Buenos Aires, Argentina, 2012.
  21. Olga Lopera and Yves Dupont. Automated Target Recognition in Synthetic Aperture Sonar: shadow and highlight-based classification. . In Oceans 2012, page 4, Hampton Roads, VA, 2012.
  22. W Mees and R Heremans. Multisensor data fusion for IED threat detection. In Proceedings of SPIE, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence VIII, volume 8546, October 2012.
  23. B Mertens, B De Leener, C Beumier, O Debeir, P Lambert, and A Delchambre. Robust Structured Light Pattern for Use with a Hologram in 3D Endoscopy. In Int. Symposium on OptoMechatronic Technologies - ISOT'12, Paris, France, 2012.
  24. C Beumier and M Idrissa. Building Change Detection by Histogram Classification. In Int. Conf. on Signal-Image Technology and Internet-based Systems - SITIS 2011, Dijon, France, 2011.
  25. Olga Lopera. ANALYSIS OF SEGMENTATION TECHNIQUES TO FACILITATE DETECTION AND IDENTIFICATION OF SEAFLOOR TARGETS. In Underwater Acoustic Measurements 2011, pages 1-4, Kos, Greece, 2011.
  26. Olga Lopera. Combining despeckling and segmentation techniques to facilitate detection and identification of seafloor targets. In Oceans 2011, pages 1-4, Santander, Spain, 2011.
  27. Francesco Soldovieri, Olga Lopera, and Sébastien Lambot. Combination of Advanced Inversion Techniques for an Accurate Target Localization via GPR for Demining Applications. IEEE Trans. on Geoscience and Remote Sensing, 49(1):451-461, 2011.
  28. C Beumier and M Idrissa. Quantitative analysis of 3D reconstruction error in the context of computational stereo in remote sensing. In GEOBIA 2010 Conference on Geographic Object-Based Image Analysis, Ghent, June 2010, June 2010.
  29. C Beumier and M Idrissa. Quantitative analysis of 3D reconstruction error in the context of computational stereo in remote sensing. In Geographic Object-Based Image Analysis - GEOBIA 2010, Ghent, Belgium, 2010.
  30. V Lacroix and M Idrissa. Optimal Palette Extraction as Part of Scanned Graphics Vectorization. In Fourth European Conference on Colour in Graphics, Imaging, and MCS/10 Vision 12th International Symposium on Multispectral Colour Science, Joensuu, Finland June 2010, June 2010.
  31. C Leignel, O Debeir, E Hanson, T Leloup, C Simler, C Beumier, G Bontempi, N Warzee, and E Wolff. Detecting man-made structure changes to assist geographic data producers in planning their update strategy. In ISPRS joint workshop on 'Core Spatial Database - Updating, Maintainance and Services', Haifa, Israel, 2010.
  32. Olga Lopera. Analysis and comparison of different SAR image speckle reduction techniques applied to SAS. In International Conference on Synthetic Aperture Sonar and Synthetic Aperture Radar, Lerici, Italy, 2010.
  33. Olga Lopera. Filtering speckle noise in SAS images to improve detection and identification of seafloor targets. In Waterside Security Conference (WSS), 2010 International, pages 1-4, Carrara, Italy, 2010.
  34. C Simler and C Beumier. Building and Road Extraction on Urban VHR Images using SVM Combinations and Mean Shift Segmentation. In Proceeding of the Int. Conf. On Computer Vision Theory and Applications - VISAPP 2010, Anger, France, 2010.
  35. C Simler and C Beumier. Performance Evaluation of a Road and Building Classifier on VHR Images. In Geographic Object-Based Image Analysis - GEOBIA 2010, Ghent, Belgium, 2010.
  36. C Beumier. Fast Dense Disparity Estimation of Stereo Couples from Image Gradient. In 5th Int. Conf. on Signal-Image Technology and Internet-based Systems - SITIS09, Marrakech, Morocco, November 2009.
  37. M Idrissa and V Lacroix. A Multiresolution-MRF Approach for Stereo Dense Disparity Estimation. In IEEE-GRSS/ISPRS Joint Urban Remote Sensing Event, May 20-22 2009, Shanghai China, May 2009.
  38. C Simler, C Beumier, C Leignel, O Debeir, and E Wolff. The use of ORFEO Toolbox in the context of map updating. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS'09, Cape Town, South Africa, 2009.
  39. A Wimmer, I Lingenfelder, C Beumier, J Inglada, and S Caseley. Feature Recognition Techniques, chapter Part III, pages 105-118. Jasani, B and Pesaresi, M and Schneiderbauer, S and Zeug, G, 2009.
  40. E Wolff, O Debeir, E Hanson, C Leignel, C Simler, C Beumier, and N Warzee. Comparaison et évaluation des méthodes de segmentation avec contrainte en vue d'une classification du bâti et des routes. In Proceedings de JIGOT, Toulouse, France, November 2009.
  41. C Beumier. Building detection in Ikonos images from disparity of edges. In Int. Conf. on Computer Vision Theory and Applications, Funchal, Madeira, January 2008.
  42. C Beumier. Building Verification from Disparity of Contour Points. In Image Processing Theory, Tools & Applications, IPTA'08, Sousse, Tunisia, November 2008.
  43. O Lopera. An Integrated Detection and Identification Methodology Applied to Ground-Penetrating Radar Data for Humanitarian Demining Applications. PhD thesis, Université catholique de Louvain, Belgium - École royale militaire, Belgium - Universidad de Los Andes, Colombia, 2008.
  44. Olga Lopera, Nada Milisavljevi, David Daniels, Alain Gauthier, and Benoît Macq. A time frequency domain feature extraction algorithm for landmine identification from GPR data. Near Surface Geophysics, 6(6):411-421, December 2008.
  45. C Beumier. Building detection from disparity of edges. In 27th EARSeL Symposium Geoinformation in Europe, Bolzano, Italy, 2007.
  46. C Beumier. Building verification from geometrical and photometric cues. In Applications of Digital Image Processing XXX, Proceedings of SPIE, volume 6696, San Diego, California, 2007.
  47. C Beumier. Building verification from geometrical features. In 27th EARSeL Symposium Geoinformation in Europe, Bolzano, Italy, 2007.
  48. C Beumier. Industrial area detection during GNEX06. In In JRC Scientific and Technical Reports, GMOSS, G. Zeug & M. Pesaresi Eds., pages PP. 361-364, 2007.
  49. O Lopera, N Milisavljevic, and S Lambot. Clutter Reduction in GPR Measurements for Detecting Shallowly Buried Landmines: a Colombian Case Study. Near Surface Geophysics, 2007.
  50. O Lopera, N Milisavljevic, B Macq, and S Lambot. Time-frequency domain signature analysis of GPR data for landmine identification. In Proceedings of the 4th International Workshop on Ground Penetrating Radar, pages 159-162, 2007.
  51. V Lacroix V. Alberga M. Idrissa and J Inglada. Comparison of similarity measures of multi-sensor images for change detection applications. In Proceedings of IGARSS 2007, Barcelona, Spain, July 2007, July 2007.
  52. V Lacroix V. Alberga M. Idrissa and J Inglada. Performance estimation of similarity measures of multi-sensor images for change detection applications. In Proceedings of MultiTemp 2007, Leuven, Belgium, July 2007, July 2007.
  53. C Beumier. 3D Face Recognition. In IEEE International Conference on Industrial Technology 2006, Mumbai, India, 2006.
  54. C Beumier. Identity Authentication through 3D Face Analysis. In Biometrics Summer School 2006, Alghero, Italy, 2006.
  55. C Beumier. Straight-line Detection Using Moment of inertia. In IEEE International Conference on Industrial Technology 2006, Mumbai, India, 2006.
  56. C Beumier and V Lacroix. Road extraction for EuroSDR contest. In Proceedings of the SPIE, Image and Signal Processing for Remote Sensing XII, volume 6365, Stockholm, Sweden, September 2006.
  57. K Mertens and W Mees. Communication and information system for disaster relief operations. In Proceedings of ISCRAM 2006 - 3rd International Conference on Information Systems for Crisis Response and Management, pages 461-464, 2006.
  58. A Hincq H Bruynseels V. Lacroix M. Idrissa and O Swartenbroekx. Detecting urbanization changes using spot5. Pattern Recognition Letters, 2006.
  59. Damien Closson. Exploiting SAR coherence in time. PhD thesis, Université de Liège, 2005.
  60. S. Delhay, V. Lacroix, and M Idrissa. Paradis: Gis tools for humanitarian demining. In ISCRAM 2005 Information Systems for Crisis Response And Management Conference, April 2005.
  61. O Lopera, S Lambot, N Milisavljevic, B Scheers, and I van den Bosch. Background Subtraction in the Frequency Domain for Focusing Ground-Penetrating Radar Data. In Proceedings of the Third International Workshop on Advanced GPR, Delft, The Netherlands, 2005.
  62. O. Lopera, S. Lambot, N. Milisavljevic, B. Scheers, and I. van den Bosch. Background subtraction in the frequency domain for focusing ground-penetrating radar data. In Proceedings of the 3rd International Workshop on Advanced Ground Penetrating Radar, pages 25-30. IEEE, 2005.
  63. A Hincq H Bruynseels V. Lacroix M. Idrissa and O Swartenbroekx. Spot5 pour la télédétection d'urbanisation. Revue Française de Photogramétrie et de Télédétection, 2005.
  64. C Beumier. 3D Face Recognition. In CIHSPS2004, Venice, Italy, 2004.
  65. C Beumier. 3D Facial Surface Capture. In PIERS2004, Nanjing, China, 2004.
  66. C Beumier. Calibration of a Structured Light System for 3D Acquisition. In SPS 2004, Hilvarenbeek, The Netherlands, 2004.
  67. C Beumier. Design of Coded Structured Light Pattern for 3D Facial Surface Capture. In EUSIPCO2004, pages 2291-2294, Vienna, Austria, September 2004.
  68. O Lopera, N Milisavljevic, B Macq, I van den Bosch, S Lambot, and A Gauthier. Analysis of segmentation techniques for landmine signature extraction from Ground Penetrating Radar 2D data. In eProceedings of the II International IEEE Andean Region Conference, ISBN 958-33-6534-3, Bogota, Colombia, 2004.
  69. A Hincq H Bruynseels V. Lacroix M. Idrissa and O Swartenbroekx. A visibility test on spot5 images. In ISPRS 2004, volume Commission 4, Istanbul, Turkey, July 2004, July 2004.
  70. C Beumier. Facial Surface Acquisition with Colour Striping. In ICANN/ICONIP 2003, pages 548-551, Istanbul, Turkey, 2003.
  71. C Beumier. Person Authentication through 3D Face Analysis. Phd thesis, ENST, Dépt. TSI, Paris, 2003.
  72. S. Delhay, V. Lacroix, and M. Idrissa. Paradis, a gis tool for the management of humanitarian demining campaigns. In EUDEM2-SCOT-2003 International Conference on Requirements and Technologies for the Detection, Removal and Neutralization of Landmines and UXO, September 2003.
  73. S Garcia-Salicetti, C Beumier, G Chollet, B Dorizzi, J Leroux les jardins, Jan Lunter, Yang Ni, and D Petrovska-Delacrétaz. BIOMET: A Multimodal Person Authentication Database Including Face, Voice, Fingerprint, Hand and Signature Modalities. In AVBPA2003, Guildford, UK, 2003.
  74. M Idrissa and M Acheroy. Texture Classification using Gabor Filters. Pattern Recognition Letters, 2002.
  75. C Beumier and M Acheroy. Face Verification from 3D and grey-level clues. Pattern Recognition Letters, 22:1321-1329, 2001.
  76. C Beumier and M Acheroy. Automatic 3D Face Authentication. Image and Vision Computing, Special Issue on Facial Image Analysis, 18(4):315-321, March 2000.
  77. C Beumier and M Acheroy. Automatic Face Recognition. In Proceedings symposium IMAGING, pages 77-89, Eindhoven, The Netherlands, 2000.
  78. C Beumier and M Acheroy. Automatic Face Verification from 3D and Grey Level Clues. In 11th Portuguese conference on pattern recognition (RECPAD2000), Porto, Portugal, 2000.
  79. C Beumier, P Druyts, Y Yvinec, and M Acheroy. Motion estimation of a hand-held mine detector. In Signal Processing Symposium, Hilvarenbeek, The Netherlands, March 2000.
  80. C Beumier, P Druyts, Y Yvinec, and M Acheroy. Real-Time Optical Position Monitoring using a Reference Bar. In Signal Processing and Communications (SPC2000), pages 468-473, Marbella, Spain, September 2000.
  81. Charles Beumier, Pascal Druyts, Yann Yvinec, and Marc Acheroy. Motion estimation of a hand-held mine detector. In Signal Processing Symposium, Hilvarenbeek, The Netherlands, March 2000.
  82. Charles Beumier, Pascal Druyts, Yann Yvinec, and Marc Acheroy. Real-time optical position monitoring using a reference bar. In Signal Processing and Communications (SPC2000), pages 468-473, Marbella, Spain, September 2000.
  83. M Idrissa and M Acheroy. An Iterative Fuzzy C-means Algorithm - Application to Landcover Classification. In 4th World Multiconference on Systemics, Cyber netics and Informatics, special session on Geographical Information Processing and Remote Sensing, Orlando, Florida(USA), July 2000.
  84. M Idrissa and M Acheroy. Texture Classification using Gabor Filters. In First International Workshop on Pattern Recognition Techniques in Remote Sensing, Andorra la Vella, Andorra, September 2000.
  85. C Beumier and M Acheroy. 3D Facial Surface Acquisition by Structured Light. In International Workshop on Synthetic-Natural Hybrid Coding and Three Dimensional Imaging, ICMCS 1999, pages 103-106, Santorini, Greece, September 1999.
  86. C Beumier and M Acheroy. SIC_DB: Multi-Modal Database for Person Authentication. In Proceedings of the 10th International Conference on Image Analysis and Processing (ICIAP), pages 704-708, Venice, Italy, September 1999.
  87. Pascal Druyts, Yann Yvinec, and Marc Acheroy. Image processing tools for semi-automatic minefield detection. In 2nd International Symposium on Operationalization of Remote Sensing (ORS99), ITC-Enschede (The Netherlands), 1999.
  88. Wim Mees. A distributed automatic scene-analysis system. PhD thesis, Institut Henri Poincaré, Paris, 1999.
  89. Y Ouaghli and X Neyt. Meteosat Specific Implementation: The wavelet compression. Technical report, Royal Military Academy / Signal & Image Centre, August 1999.
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