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Contour matching using wavelet transform and multigrid methods

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Abstract

In this paper, wavelet transform and multigrid method are combined to make the method more practical. It is known that Gaussian filtering causesshrinkage of data. To overcome this disadvantage, Gaussian filtering is replaced with wavelet transform. This method introduces no curve shrinkage. Then, the linearized form of objective equation is proposed. This makes contour matching easier to implement. Finally, the multigrid method is used to speed up the convergence.

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Author information

Authors and Affiliations

  1. School of Mathematics, The University of New South Wales, 2052, Sydney, Australia

    Jiang Tianzi

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100080, Beijing

    Ma Songde

Authors
  1. Jiang Tianzi
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  2. Ma Songde
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Corresponding author

Correspondence to Jiang Tianzi.

Additional information

Project supported by the National Natural Science Foundation of China and the National Key Fundamental Research Program of China.

Tianzi Jiang was born in 1962. He received his B.S. degree in computational mathematics from Lanzhou University in 1984, and his M.S. and Ph.D degrees in computational mathematics from Hangzhou University in 1992 and 1994, respectively. From 1994 to 1996 he worked as a postdoctoral fellow in National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences. Now he is an Associate Professor in NLPR. He is a member of New York Academy of Sciences. He has authored and coauthored more than 30 reviewed papers on computer vision, pattern recognition, computational complexity and applied mathematics.

For the biography of Ma Songde, please refer to p.57, Vol. 12, No. 1 of this journal.

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Jiang, T., Ma, S. Contour matching using wavelet transform and multigrid methods. J. of Comput. Sci. & Technol. 12, 564–570 (1997). https://doi.org/10.1007/BF02947208

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  • DOI: https://doi.org/10.1007/BF02947208

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