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Surface Extraction from Multi-Material Components for Metrology using Dual Energy CT
November/December 2007 (vol. 13 no. 6)
pp. 1520-1527
This paper describes a novel method for creating surface models of multi-material components using dual energy computed tomography (DECT). The application scenario is metrology and dimensional measurement in industrial high resolution 3D x-ray computed tomography (3DCT). Based on the dual source / dual exposure technology this method employs 3DCT scans of a high precision micro-focus and a high energy macro-focus x-ray source. The presented work makes use of the advantages of dual x-ray exposure technology in order to facilitate dimensional measurements of multi-material components with high density material within low density material. We propose a workflow which uses image fusion and local surface extraction techniques: a prefiltering step reduces noise inherent in the data. For image fusion the datasets have to be registered. In the fusion step the benefits of both scans are combined. The structure of the specimen is taken from the low precision, blurry, high energy dataset while the sharp edges are adopted and fused into the resulting image from the high precision, crisp, low energy dataset. In the final step a reliable surface model is extracted from the fused dataset using a local adaptive technique. The major contribution of this paper is the development of a specific workflow for dimensional measurements of multi-material industrial components, which takes two x-ray CT datasets with complementary strengths and weaknesses into account. The performance of the workflow is discussed using a test specimen as well as two real world industrial parts. As result, a significant improvement in overall measurement precision, surface geometry and mean deviation to reference measurement compared to single exposure scans was facilitated.

[1] P. J. Burt, The pyramid as a structure for efficient computation. In A. Rosenfeld, editor, Multiresolution Image Processing and Analysis, pages 6–35. Springer-Verlag, 1984.
[2] S. F. F. Gibson, Constrained elastic surface nets: generating smooth surfaces from binary segmented data. In MICCAI '98: Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 888–898, 1998.
[3] C. Heinzl, R. Klingesberger, J. Kastner, and E. Gröller, Robust surface detection for variance comparison. In Proceedings of Eurographics/IEEEVGTC Symposium on Visualisation, pages 75–82, 2006.
[4] J. Hsieh, Computed Tomography: Principles, Design, Artifacts and Recent Advances. SPIE-The International Society for Optical Engineering, 2003.
[5] R. Huang, K.-L. Ma, P. McCormick, and W. Ward, Visualizing industrial CT volume data for nondestructive testing applications. In VIS '03: Proceedings of the 14th IEEE Visualization 2003 (VIS'03), pages 547–554, 2003.
[6] L. Ibanez, W. Schroeder, L. Ng, and J. Cates, The ITK Software Guide. Kitware, Inc. ISBN 1-930934-10-6, http://www.itk.orgItkSoftwareGuide.pdf, first edition, 2003.
[7] M. Iovea, O. Duliu, G. Oaie, C. Ricman, and G. Mateiasi, Dual-energy computer tomography and digital radiography investigation of organic and inorganic materials. In Proceedings of European Conference on Non Destructive Testing, 2006.
[8] S. Kasperl, Qualitätsverbesserungen durch referenzfreie Artefaktreduzierung und Oberflächennormierung in der industriellen 3D-Computertomographie. PhD thesis, Technische Fakultät der Universität Erlangen Nürnberg, 2005.
[9] J. Kastner, E. Schlotthauer, P. Burgholzer, and D. Stifter, Comparison of x-ray computed tomography and optical coherence tomography for characterisation of glass-fibre polymer matrix composites. In Proceedings of World Conference on Non Destructive Testing, pages 71–79, 2004.
[10] G. Kindlmann and J. W. Durkin, Semi-automatic generation of transfer functions for direct volume rendering. In IEEE Symposium on Volume Visualization, pages 79–86, 1998.
[11] J. Kniss, G. Kindlmann, and C. Hansen, Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets. In VIS '01: Proceedings of the conference on Visualization '01, pages 255–262, Washington, DC, USA, 2001. IEEE Computer Society.
[12] J. J. Lewis, R. J. OCallaghan, S. G. Nikolov, D. R. Bull, and C. N. Canagarajah, Region-based image fusion using complex wavelets. In Proceedings of the Seventh International Conference on Information Fusion, volume I, pages 555–562, 2004.
[13] H. Li, B. S. Manjunath, and S. K. Mitra, Multisensor image fusion using the wavelet transform. In Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference, volume 1, pages 51–55, 1994.
[14] Y. O. L.J. Chipman and L. Graham, Wavelets and image fusion. In Proceedings of the International Conference on Image Processing, pages 248–251, 1995.
[15] W. Lorensen and H. Cline, Marching cubes: a high resolution 3D surface construction algorithm. In ACM SIGGRAPH Computer Graphics, volume 21, pages 163–169, 1987.
[16] D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen, and W. Eubank, Non-rigid multimodality image registration. In Medical Imaging 2001: Image Processing, pages 1609–1620, 2001.
[17] D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen, and W. Eubank, PET-CT image registration in the chest using free-form deformations. In IEEE Transactions in Medical Imaging, volume 22, pages 120–128, 2003.
[18] S. Nikolov, P. Hill, D. Bull, and C. Canagarajah, Wavelets in Signal and Image Analysis, chapter Wavelets for image fusion, pages 213–244. Kluwer Academic Publishers, The Netherlands, 2001.
[19] N. Otsu, A threshold selection method from grey level histograms. In IEEE Transactions on Systems, Man, and Cybernetics, volume 9, 1979.
[20] P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 12, pages 629–639, 1990.
[21] V. Petrovic and C. Xydeas, Gradient-based multiresolution image fusion. In IEEE Transactions on Image Processing, volume 13, pages 228–237, 2004.
[22] V. Rebuffel and J.-M. Dinten, Dual-energy x-ray imaging: benefits and limits. In Proceedings of European Conference on Non Destructive Testing, 2006.
[23] W. Schroeder, K. Martin, and B. Lorensen, The Visualization Toolkit. Kitware, Inc., 2004.
[24] J. Sethian, Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision and Materials Sciences. Cambridge University Press, second edition, 1999.
[25] H. Steinbeiss, Dimensionelles Messen mit Mikro-Computertomographie. PhD thesis, Technische Universität München, 2005.
[26] B. M. ter Haar Romeny, Geometry Driven Diffusion in Computer Vision. Series on Computational Imaging and Vision. Kluwer Academic Publishers, Dordrecht, the Netherlands, 1994.
[27] VolumeGraphics. VG Studio Max 1.2 - User's Manual. 2004.
[28] R. T. Whitaker, Reducing aliasing artifacts in iso-surfaces of binary volumes. In VVS '00: Proceedings of the 2000 IEEE Symposium on Volume visualization, pages 23–32, 2000.
[29] R. T. Whitaker and D. E. Breen, Level-set models for the deformation of solid objects. In The third international workshop on implicit surfaces, pages 19–35, 1998.
[30] Wikipedia. Metrology. Wikipedia: WWW:http://en.wikipedia.orgwiki/ Metrology, March18th 2007.
[31] M. L. Williams, R. C. Wilson, and E. R. Hancock, Deterministic search for relational graph matching. Pattern Recognition, 32 (7): 1255–1271, 1999.

Index Terms:
DECT image fusion, local surface extraction, Dual Energy CT, metrology, dimensional measurement, variance comparison.
Citation:
Christoph Heinzl, Johann Kastner, Eduard Gröller, "Surface Extraction from Multi-Material Components for Metrology using Dual Energy CT," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1520-1527, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70598
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