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Proceedings Paper

Removal of defects on flash radiographic images by fuzzy combination
Author(s): Nathalie Combier; Isabelle Dauty; Jacques Lemoine
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Paper Abstract

We present a method for automatic detection and removal of defects on flash X-ray images. In our experiments, we obtain about ten images representing the radiographic projection of the same object. Defects appear on some images and limit the measurement accuracy. Our aim is to assess the radiant image (image before detection) by combining the relevant information on the different radiographs. First, we isolate the defects from the object projection by the point by point difference between two images. Then, a multiscale filtering is performed on the difference images to extract the defects according to their spatial extent. Next, each filtered image is segmented by a fuzzy clustering method which takes into account inaccurate edges of the defects. The resultant fuzzy images indicate the defect importance on the difference images by a degree between 0 and 1. Afterwards, the fuzzy images obtained are aggregated to retrieve the fuzzy relevance degrees of the measurement on each original image. Finally, the defects are removed by a fuzzy combination of the images according to their relevance degrees. On the resultant images, the defects are well suppressed thanks to the selection of the reliable information.

Paper Details

Date Published: 27 March 1995
PDF: 12 pages
Proc. SPIE 2423, Machine Vision Applications in Industrial Inspection III, (27 March 1995); doi: 10.1117/12.205517
Show Author Affiliations
Nathalie Combier, CEA/CEV-M and Univ. Paris Val-de-Marne (France)
Isabelle Dauty, CEA/CEV-M (France)
Jacques Lemoine, Univ. Paris Val-de-Marne (France)


Published in SPIE Proceedings Vol. 2423:
Machine Vision Applications in Industrial Inspection III
Frederick Y. Wu; Stephen S. Wilson, Editor(s)

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