Abstract
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.
This work was supported by the INCO-COPERNICUS grant IC15 CT 96-0742.
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© 1999 Springer-Verlag Berlin Heidelberg
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Chetverikov, D., Khenokh, Y. (1999). Matching for Shape Defect Detection. In: Solina, F., Leonardis, A. (eds) Computer Analysis of Images and Patterns. CAIP 1999. Lecture Notes in Computer Science, vol 1689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48375-6_44
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DOI: https://doi.org/10.1007/3-540-48375-6_44
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