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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
G. Borgefors. Distance transforms in arbitrary dimensions. Computer Vision, Graphics and Image Processing, 27:321–345, 1984.
D. Chetverikov. Fast neighborhood search in planar point set. Pattern Recognition Letters, 12:409–412, 1991.
P.J. Rousseeuw and A.M. Leroy. Robust Regression and Outlier Detection. Wiley Series in Probability and Mathematical Statistics, 1987.
W.J. Rucklidge. Efficiently Locating Objects Using the Hausdorff Distance. International Journal of Computer Vision, 24(3):251–270, 1997.
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.
J. Verestoy and D. Chetverikov. Shape defect detection in ferrite cores. Machine Graphics and Vision, 6(2):25–236, 1997.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/3-540-48375-6_44
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66366-9
Online ISBN: 978-3-540-48375-5
eBook Packages: Springer Book Archive