Accuracy Estimation of Detection of Casting Defects in X-Ray Images Using Some Statistical Techniques

  • Romeu Ricardo da Silva
  • Domingo Mery
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)

Abstract

Casting is one of the most important processes in the manufacture of parts for various kinds of industries, among which the automotive industry stands out. Like every manufacturing process, there is the possibility of the occurrence of defects in the materials from which the parts are made, as well as of the appearance of faults during their operation. One of the most important tools for verifying the integrity of cast parts is radioscopy. This paper presents pattern recognition methodologies in radioscopic images of cast automotive parts for the detection of defects. Image processing techniques were applied to extract features to be used as input of the pattern classifiers developed by artificial neural networks. To estimate the accuracy of the classifiers, use was made of random selection techniques with sample reposition (Bootstrap technique) and without sample reposition. This work can be considered innovative in that field of research, and the results obtained motivate this paper.

Keywords

Casting Defects Radioscopy Image Processing Accuracy Estimation Bootstrap 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Romeu Ricardo da Silva
    • 1
  • Domingo Mery
    • 1
  1. 1.Departamento de Ciencia de la Computación, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860 (143) 

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