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標題: 頻率域多視角形貌註冊
Multiview Range Image Registration By A Frequency Domain Technique
作者: 胡育維
Hu, Yu-Wei
關鍵字: FFT;快速傅立葉轉換;Registration;Phase correlation;ICP algorithm;影像註冊;相位關聯法;ICP演算法
出版社: 機械工程學系所
引用: 參考文獻 1. P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes, ” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 239-256, 1992. 2. J. W. Cooley and O. W Tukey, “An Algorithm for the Machine Calculation of Complex Fourier Series. ” Math. Comput., 19,pp 297-301.1965 3. E. De Castro and C. Morandi, “Registration of translated and rotated images using finite Fourier transforms,” IEEE Truns. Pattern Anal. Muchine Intell., vol. PAMI-95, pp. 700-703, Sept. 1987. 4. L . Lucchese and G.M. Cortelazzo, “A Noise-Robust Frequency Domain Technique for Estimating Planar Roto-Translations,” IEEE Trans. Signal Processing, vol. SP-48, no. 6, pp. 1769-1786,June 2000. 5. L .Lucchese, G.M. Cortelazzo, and C. Monti, “High Resolution Estimation of Planar Rotations Based on Fourier Transform and Radial Projections,” Proc. Int’l Symp. Circuits and Systems 1997,vol. II, pp. 1181-1184, June 1997. 6. L. Lucchese, G.. Doretto, and G.M. Cortelazzo, “Frequency Domain Estimation of 3D Rigid Motion Based on Range and Intensity Data,” Proc. Int’l Conf. Recent Advances in 3D Digital Imaging and Modeling, pp. 107-112, May 1997. 7. G.M. Cortelazzo, G.. Doretto, and L. Lucchese, “Free-Form Textured Surfaces Registration by a Frequency Domain Technique,” Proc. IEEE Int’l Conf. Image Processing, vol. 1, pp. 813-817,Oct. 1998. 8. Y. Keller, A. Averbuch, Y. Shkolnisky: “Algebraically Accurate Volume Registration Using Euler''s Theorem and the 3-D Pseudo-Polar FFT, ”CVPR pp.795-800,2005: 9. Y. Keller, Y. Shkolnisky, and A. Averbuch. “ The angular difference function and its application to image registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, ”pp.969–976, 2005 10. Y. Keller, Y. Shkolnisky, and A. Averbuch. “Volume registration using the 3-D pseudo-polar Fourier transform. ”IEEE Transactions on Signal Processing, 54(11):4323–4331, 2006. 11. B. Srinivasa Reddy and B. N. Chatterji. “An FFT-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration,”pp.1266-1271,Aug,1996 12. Y. Keller, A. Averbuch. “A Projection-Based Extension of the Phase Correlation Method” Signal Processing , ” Volume 87, Issue 1 , pp. 124-133,January 2007. 13. C.D. Kuglin and D.C. Hines, “The Phase Correlation Image Alignment Method,” Proc. IEEE 1975 Int’l Conf. Cybernetics and Soc., pp. 163-165, Sept. 1975. 14. J. Feldmar and N. Ayache, “Rigid, Affine, and Locally Affine Registration of Free-Form Surfaces,” Int’l J. Computer Vision, vol. 18, no. 2, pp. 99-119, 1996. 15. R.N. Bracewell, K.-Y. Chang, A.K. Jha, and Y.-H. Wang, “Affine Theorem for Two-dimensional Fourier Transform,” Electronics Letters, vol. 29, no. 3, p. 304, Feb. 1993.

In the age of rapid progress of industrialization, it is a popular methodology to utilize range images for 3D objects reconstruction, eg, use computer tomography (CT) to rebuild human bone structures.
This paper introduces an algorithm for the registration of rotated and translated object using the three-dimensional (3-D) Fast Fourier transform. The Fourier transform allow the decoupling of the estimate of the rotation parameters from the estimate of the translation parameters. The rotation estimation is based on Euler's theorem, which allows one to represent a 3-D rotation as a planar rotation around a 3-D rotation axis. We propose a three-step procedure. The first step estimates the rotation axis. The second step computes the planar rotation relative to the rotation axis. The third step recovers the translational displacement by phase correlation technique. This method is fast and does not require an initial estimation. This algorithm can be used as prealignment tool for more accurate space domain registration techniques, like the ICP algorithm.
其他識別: U0005-0408200810055300
Appears in Collections:機械工程學系所

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