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Research on the Application of ICP Algorithm in Spatial Registration of Computer-Aided Surgery

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Abstract:

This paper discusses the surface profile method based on image registration, and illustrates the principle and key points of registration algorithm based on surface profile. Canny operator is adopted to extract the surface contour and method based on quaternion and the singular value decomposition is used for space registration of the corresponding points, as well as the closest iterative search (ICP). In order to improve the registration speed, we adopt multiple step iteration method, which has been proved to be a reliable method according to the experiment.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

4061-4066

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.4061

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Cite this paper

Online since:

August 2013

Authors:

Yun Tao Wei

Keywords:

Computer Aided, ICP, Registration, Surgery

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] B. K. P. Horn, B. G. Schunk. Determing optical flow[J]. Artificial Intelligence, 2007. 17: 185-203.

Google Scholar

[2] K. S. Arun, T. S Huang, S. D. Blostein. Least-squares fitting of two 3-D point sets[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007. 9(5): 698-700.

DOI: 10.1109/tpami.1987.4767965

Google Scholar

[3] Paul J. Besl, Neil D. McKay. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002. 14(2): 239-256.

DOI: 10.1109/34.121791

Google Scholar

[4] Y. Chen, G. Medioni. Object Modeling by Registration of Multiple Range Images[J]. Image and Vision Computing, 2002. 10: 145-155.

DOI: 10.1016/0262-8856(92)90066-c

Google Scholar

[5] R. Bergevin, M Soucy, H. Gagnon, et al. Towards a general multi-view registration technique[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996. 18(5): 540-547.

DOI: 10.1109/34.494643

Google Scholar

[6] Andrew Edie Johnson, Sing Bing Kang. Registration and Integration of Textured 3D Data[J]. Image and Vision Computing, 2009. 17: 135-147.

DOI: 10.1016/s0262-8856(98)00117-6

Google Scholar

[7] Natasha Gelfand, Leslie Ikemoto, Szymon Rusinkiewicz, et al. Geometrically Stable Sampling for the ICP Algorithm[A]. Proceedings of Fourth International Conference on 3-D Digital Imaging and Modeling[C]. Stanford University, CA, USA, 2003: 260-267.

DOI: 10.1109/im.2003.1240258

Google Scholar

[8] P.J. Besl, H.D. McKay. A Method for Registration of 3D Shape[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002. 14(2): 239-256.

DOI: 10.1109/34.121791

Google Scholar

[9] Qin Binjie, Zhuang Tiange. The Method of Using the Correlation Ratio Similarity Measure Multi-resolution for registration MR and CT Medical Images. Chinese Biomedical Engineering Journal, 2003，22(1)：1-5.

Google Scholar