Matching for Shape Defect Detection

  • Dmitry Chetverikov
  • Yuri Khenokh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1689)


The problem of defect detection in 2D and 3D shapes is analyzed. A shape is represented by a set of its contour, or surface, points. Mathematically, the problem is formulated as a specific matching of two sets of points, a reference one and a measured one. Modified Hausdorff distance between these two point sets is used to induce the matching. Based on a distance transform, a 2D algorithm is proposed that implements the matching in a computationally efficient way. The method is applied to visual inspection and dimensional measurement of ferrite cores. Alternative approaches to the problem are also discussed.


Defect Detection Robust Regression Distance Transform Reference Shape Ferrite Core 
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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  1. 1.
    G. Borgefors. Distance transforms in arbitrary dimensions. Computer Vision, Graphics and Image Processing, 27:321–345, 1984.CrossRefGoogle Scholar
  2. 2.
    D. Chetverikov. Fast neighborhood search in planar point set. Pattern Recognition Letters, 12:409–412, 1991.CrossRefGoogle Scholar
  3. 3.
    P.J. Rousseeuw and A.M. Leroy. Robust Regression and Outlier Detection. Wiley Series in Probability and Mathematical Statistics, 1987.Google Scholar
  4. 4.
    W.J. Rucklidge. Efficiently Locating Objects Using the Hausdorff Distance. International Journal of Computer Vision, 24(3):251–270, 1997.CrossRefGoogle Scholar
  5. 5.
    The SQUASH Consortium. Standard-compliant Quality Control System for High-level Ceramic Material manufacturing. Technical report, EU INCO-COPERNICUS Programme, Project IC15 CT 96-0742, 1998.Google Scholar
  6. 6.
    J. Verestoy and D. Chetverikov. Shape defect detection in ferrite cores. Machine Graphics and Vision, 6(2):25–236, 1997.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Dmitry Chetverikov
    • 1
  • Yuri Khenokh
    • 1
  1. 1.Computer and Automation Research Institute1111 BudapestHungary

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