Abstract
The paper presents a work developed in the framework of the two years COPERNICUS technological research project CRASH (CRack and SHape defect detection in ferrite cores) CIPA-CT94 0I53, in progress since 1995.
The CRASH project concerns automated quality inspection of ferrite cores. CRASH studies the development of optical and electromagnetic systems that may be integrated in a working module to increase the recognition of imperfections on ferrite materials. Analysis and processing of acquired images and signals, as well as specification of ad-hoc algorithms for classification purposes constitute the technical approach to the problem. The achieved results show the capability of the system to detect different kind of imperfections in ferrite cores (shape defects, surface defects and subsurface imperfections) and classify them with low error rates.
After an introduction to the problem in Section 1, different techniques of defect detection with different sensors are shown in Section 2, and Section 3 describes the achieved classification results.
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
The CRASH project official home page is at http://www.Iii.unitn.it The CRASH Consortium: UNT University of Trento, Rovereto ITALY-Project Coordinator HAS Hungarian Academy of Sciences, Budapest HUNGARY PAS Polish Academy of Sciences, Warsaw POLAND AIP Association of Image Processing, Warsaw POLAND TSC Technical Software Consultant Ltd., Milton Keynes UK POLFER POLFER Magnetic Materials, Warsaw POLAND.
D. Mirshekar-Syahkal, R. Collins and D. H. Michael, “Developments in surface cracks by the A.C. field technique”, Review of progress in quantitative NDT Evaluation, Donald O. Thompson et al. eds., Plenum Publishing, 1985, pp. 349–357.
M. Nieniewski, Morphological Method of Detection of defects on the Surface of Ferrite Cores, Proc. 10th Scandinavian Conference on Image Analysis, Lappeenranta, Jun 1997.
K. I. Laws, Textured image segmentation, Univ. of Southern California, Image Processing Institute, USCIPI Report 940, Jan 1980.
W. K. Pratt, Digital Image Processing, John Wiley, New York 1991.
C-M. Wu, Y-C. Chen, Statistical feature matrix for texture analysis, CVGIP: Graphical Models and Image Processing, 54, 5, 1992, pp. 407–419.
A.Jozwik, L.Chmielewski, W.Cudny, M.Sklodowski, A 1-NN preclassifier for fuzzy k-NN rule, Proc. 13th Int. Conf. Pattern Recognition, ICPR96, Wien, Austria, August 1996, Track D, pp. 234–238.
Z. Wu, “Homogeneity testing for unlabeled data: a performance evaluation”, Graphical Models and Image Processing, vol.55, September 1993, pp.370–380.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mari, M. et al. (1997). The CRASH project: Defect detection and classification in ferrite cores. In: Del Bimbo, A. (eds) Image Analysis and Processing. ICIAP 1997. Lecture Notes in Computer Science, vol 1311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63508-4_196
Download citation
DOI: https://doi.org/10.1007/3-540-63508-4_196
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63508-6
Online ISBN: 978-3-540-69586-8
eBook Packages: Springer Book Archive