Abstract
An original and efficient method to segment and label horizontal structures in 3D seismic images is presented. It is based on a morphological hierarchical segmentation. The initial extracted surfaces are post-processed using the topological segmentation method proposed by Malandain et al [1]. A last post-processing step allows to separate remaining multi-layered surfaces.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Malandain, G., Bertrand, G., Ayache, N.: Topological segmentation of discrete surfaces. International Journal of Computer Vision 10(2), 183–197 (1993)
Faucon, T., Decenciére, E., Magneron, C.: Morphological segmentation applied to 3D seismic data. In: Ronse, C., Najman, L., Decenciére, E. (eds.) Mathematical Morphology: 40 Years On. Computational Imaging and Vision, pp. 475–484 (2005)
Taner, M.: Attributes revisited. Rock Solid Image Houston Texas (1992)
Bakker, P.: Image structure analysis for seismic interpretation. PhD thesis, Technische Universiteit Delft (2002)
Bouchereau, I.B.: Analyse d’images par transformée en ondelettes; application aux images sismiques. PhD thesis, Université Joseph Fourier Grenoble (1997)
Hale, D., Emmanuel, J.: Seismic interpretation using global image segmentation. In: 73th Annual International Meeting, Society of Exploration Geophysicists (2003)
Valet, L., Mauris, G., Bolon, P., Keskes, N.: Seismic image segmentation by fuzzy fusion of attributes. IEEE Transactions on Instrumentation and Measurement 50, 1014–1018 (2001)
Moueddene, K.: Analyse d’images en sismique: pretraitement et extraction d’informations par la morphologie mathématique. PhD thesis, Université Paul Sabatier, Toulouse, France (1987)
N’Guyen, M.: Analyse multi-dimensionnelle et analyse par les ondelettes des signaux sismiques. PhD thesis, Institut National Polytechnique de Grenoble (2000)
Beucher, S., Lantuéjoul, C.: Use of watersheds in contour detection. In: International workshop on image processing, real-time edge and motion detection (1979)
Meyer, F.: Minimal spanning forests for morphological segmentation. In: Serra, J., Soille, P. (eds.) Mathematical Morphology and its applications to signal processing (Proceedings ISMM 1994), Fontainebleau, France. Kluwer Academic Publishers, Dordrecht (1994)
Beucher, S.: Decenciére, E., Sandjivy, L., Magneron, C., Faucon, T.: Demande de brevet français no 05 03793 pour un procédé de détermination hiérarchique d’événements cohérents dans une image sismique
Kong, T., Rosenfeld, A.: Digital topology: Introduction and survey. Computer Vision, Graphics, And Image Processing 48(1), 357–393 (1989)
Svensson, S., Nyström, I., di Baja, G.S.: Curve skeletonization of surface-like objects in 3d images guided by voxel classification. Pattern Recognition Letter 23, 1419–1426 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Faucon, T., Decencière, E., Magneron, C. (2006). Application of Surface Topological Segmentation to Seismic Imaging. In: Kuba, A., Nyúl, L.G., Palágyi, K. (eds) Discrete Geometry for Computer Imagery. DGCI 2006. Lecture Notes in Computer Science, vol 4245. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11907350_43
Download citation
DOI: https://doi.org/10.1007/11907350_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47651-1
Online ISBN: 978-3-540-47652-8
eBook Packages: Computer ScienceComputer Science (R0)