Two types of improvements are especially awaited in NDT: a better testing of structure materials (austenitic steels, composite materials, concrete, etc. ) as they pose important problems due to their anisotropy and/or their heterogeneity (heterogeneousness), and, an automatic diagnosis in the case of very large scale testing (nuclear field). We present four examples of improvements in testing resulting from the application of digital image processing:
- the first one concerns improvements in the detection of defects in large grain size materials such as austenitic stainless steels. Image processing tries to find a certain determinism in the spatial and temporal evolution of the ultrasonic image in the presence of a defect.
- the second one gives solutions for the automatic analysis of ultrasonic images or eddy current images. In this example we use a very useful image processing tool: the concurrence matrix. An automatic thresholding method has been developed to separate defects echoes from background noise.
- the third example shows how the creation of an image "setting time-frequency" may help to solve specific problem such as the analysis of delay in manipulation of special concrete used in the construction of
- the last one applies to digital radioscopic images. It concerns the quality testing of a weld by an automatic characterization (position, dimensions) of its profiles. The image processing is founded on the active contour model. This method uses the capacity of the B-Spline deformations to represent borders of the searched profiles.
This list of examples shows how our approach by image analysis can contribute to solving major problems with the quality control of structural materials. In addition we invoke data fusion, which will be a major area of research in NDT over the next decade.
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