NDT.net - December 2002, Vol. 7 No.12

CLASSIFICATION OF POTENTIAL DEFECTS IN THE AUTOMATIC INSPECTION OF ALUMINIUM CASTINGS USING STATISTICAL PATTERN RECOGNITION

Domingo Mery
Departamento de Ingeniería Informática
Universidad de Santiago de Chile
Av. Ecuador 3659 Santiago de Chile
( dmery@ieee.org, http://www.diinf.usach.cl/~dmery/)
Dieter Filbert
Institut für Energie und Automatisierungstechnik
Technische Universität Berlin
Einsteinufer 19, D-10587 Berlin
( dieter.filbert@tu-berlin.de, http://mt.tu-berlin.de/~filbert/)
Paper presented at the 8th ECNDT, Barcelona, June 2002

Abstract

1. Introduction

2. Segmentation of potential flaws

3. Feature extraction

4. Classification

5. Conclusion and Future Directions

Acknowledgment

References

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  9. [Mery01] D. Mery: Automated Flaw Detection in Castings from Digital Radioscopic Image Sequences, Dr. Köster Verlag, Berlin, (Ph.D. Thesis in German), 2001.
  10. [Mery02a] D. Mery and D. Filbert: Automated Inspection of Moving Aluminium Castings. In Proceedings of the 8th European Conference on Non-Destructive Testing (ECNDT 2002), Jun. 17-21, 2002, Barcelona, Spain.
  11. [Mery02b] D. Mery, D. Filbert and Th. Jaeger: Image Processing for Fault Detection in Aluminum Castings. In "Analytical Characterization of Aluminum and its Alloys", Editors: D.S. McKenzie and G.E. Totten, Marcel Dekker Inc., USA, 2002.
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