Efficient registration for precision inspection of free-form surfaces

  • Liang Zhu
  • Jacob Barhak
  • Vijay Srivatsan
  • Reuven Katz

DOI: 10.1007/s00170-005-0370-9

Cite this article as:
Zhu, L., Barhak, J., Srivatsan, V. et al. Int J Adv Manuf Technol (2007) 32: 505. doi:10.1007/s00170-005-0370-9


Precision inspection of free-form surface is difficult with current industry practices that rely on accurate fixtures. Alternatively, the measurements can be aligned to the part model using a geometry-based registration method, such as the iterative closest point (ICP) method, to achieve a fast and automatic inspection process. This paper discusses various techniques that accelerate the registration process and improve the efficiency of the ICP method. First, the data structures of approximated nearest nodes and topological neighbor facets are combined to speed up the closest point calculation. The closest point calculation is further improved with the cached facets across iteration steps. The registration efficiency can also be enhanced by incorporating signal-to-noise ratio into the transformation of correspondence sets to reduce or remove the noise of outliers. Last, an acceleration method based on linear or quadratic extrapolation is fine-tuned to provide the fast yet robust iteration process. These techniques have been implemented on a four-axis blade inspection machine where no accurate fixture is required. The tests of measurement simulations and inspection case studies indicated that the presented registration method is accurate and efficient.


Optical inspection Registration between point set and CAD model ICP algorithm Approximated nearest node Simulated measurement 



Blade inspection machine


Computer aided design


Coordinate measuring machine


Iterate closest point


Measurement coordinate system


Part coordinate system


Root mean square


Signal to noise ratio

Copyright information

© Springer-Verlag London Limited 2006

Authors and Affiliations

  • Liang Zhu
    • 1
  • Jacob Barhak
    • 1
  • Vijay Srivatsan
    • 1
  • Reuven Katz
    • 1
  1. 1.NSF Engineering Research Center for Reconfigurable Manufacturing Systems, College Of EngineeringUniversity Of MichiganAnn ArborUSA

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