Pattern Recognition and Image Analysis

, Volume 17, Issue 2, pp 199–203 | Cite as

Synthesising surface matching algorithms using the correspondence framework

  • B. M. Planitz
  • A. J. Maeder
  • J. A. Williams
Image Processing, Analysis, Recognition, and Understanding


Computer vision tasks such as registration, modeling and object recognition, are becoming increasingly useful in industry. Each of these applications employs correspondence algorithms to compute accurate mappings between partially overlapping surfaces. In industry, it is essential to select an appropriate correspondence algorithm for a given surface matching task. A correspondence framework has recently been proposed to assist in the selection and creation of correspondence algorithms for these tasks. This paper demonstrates how to use the correspondence framework to create a new surface matching algorithm, which uses stages of an existing model matching algorithm. The efficiency with which the new algorithm is created using the correspondence frame work is emphasized. In addition, results show that the new algorithm is both robust and efficient.


Iterative Close Point Local Match Surface Match Iterative Close Point Algorithm Correspondence Algorithm 
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.


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Copyright information

© Pleiades Publishing, Ltd. 2007

Authors and Affiliations

  • B. M. Planitz
    • 1
  • A. J. Maeder
    • 1
  • J. A. Williams
    • 2
  1. 1.e-Health Research Centre/CSIRO ICT CentreBrisbaneAustralia
  2. 2.School of Information Technology and Electrical EngineeringUniversity of QueenslandSt. LuciaAustralia

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