Paper
27 March 1995 Removal of defects on flash radiographic images by fuzzy combination
Nathalie Combier, Isabelle Dauty, Jacques Lemoine
Author Affiliations +
Proceedings Volume 2423, Machine Vision Applications in Industrial Inspection III; (1995) https://doi.org/10.1117/12.205517
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nathalie Combier, Isabelle Dauty, and Jacques Lemoine "Removal of defects on flash radiographic images by fuzzy combination", Proc. SPIE 2423, Machine Vision Applications in Industrial Inspection III, (27 March 1995); https://doi.org/10.1117/12.205517
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Cited by 1 scholarly publication and 2 patents.
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KEYWORDS
Fuzzy logic

Digital filtering

Image filtering

Radiography

Defect detection

Image segmentation

Absorbance

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