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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Larsen, Rasmus
Technical University of Denmark
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Topics
Publications (11/11 displayed)
- 2015Dictionary Based Segmentation in Volumescitations
- 2014Surface Detection using Round Cutcitations
- 2014Pattern recognition approach to quantify the atomic structure of graphenecitations
- 2014Structure Identification in High-Resolution Transmission Electron Microscopic Imagescitations
- 2014Quantification Tools for Analyzing Tomograms of Energy Materials
- 2013Automated Structure Detection in HRTEM Images: An Example with Graphene
- 2013Quantitative Analysis of Micro-Structure in Meat Emulsions from Grating-Based Multimodal X-Ray Tomography
- 2012Large scale tracking of stem cells using sparse coding and coupled graphs
- 2010Quantitative data analysis methods for 3D microstructure characterization of Solid Oxide Cells
- 2002Building and Testing a Statistical Shape Model of the Human Ear Canal
- 2002Testing for Gender Related Size and Shape Differences of the Human Ear canal using Statistical methods
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document
Surface Detection using Round Cut
Abstract
We propose an iterative method for detecting closed surfaces in a volumetric data, where an optimal search is performed in a graph build upon a triangular mesh. Our approach is based on previous techniques for detecting an optimal terrain-like or tubular surface employing a regular grid.Unlike similar adaptations for triangle meshes, our method is capable of capturing complex geometries by iteratively refining the surface, where we obtain a high level of robustness by applying explicit mesh processing to intermediate results. Our method uses on-surface data support, but it also exploits data information about the region inside and outside the surface. This provides additional robustness to the algorithm.We demonstrate the capabilities of the approach by detecting surfaces of CT scanned objects.