Development of a New Method for the Inspection of a 3D Volume of Ultrasonic Data
NDT technologies by ultrasounds are in constant progress. The advance is considerable for sensors and acquisition systems. The means for data processing follow this evolution. In order to meet the demand for processing very high volumes of data, we propose in this paper a method of volume automatic thresholding. The application concerns the testing of austenitic steel or else, for the nuclear industry. The thresholding techniques from the image histogram are inadequate as the ultrasonic image histogram is unimodal. The study of the image with the cooccurrence matrix which is a two dimensionnal histogram allows to clearly show the noise-defect transition. Several authors have elaborated on thresholding techniques of an image from the cooccurrence matrix. These vary according to the type of exploited image [1–2]. We showed the good results of thresholding by cooccurrence matrix on images with a defect. We develop in this paper a two-part study. Firstly, after a brief account of the matrix exploitation, we show the limits of this method in bearing simulated images. We then describe the chosen approach to extend the method to the volume thresholding problem. We give results from a data volume obtained on austenitic steel testing.
KeywordsCooccurrence Matrix Thresholding Method Ultrasonic Image Thresholding Technique Cooccurrence Matrice
Unable to display preview. Download preview PDF.
- 2.J. Moysan, Imagerie numérique ultrasonore pour la détection automatique de défauts en contrôle non destructif, PhD Thesis, INSA Lyon, France, 1992.Google Scholar
- 3.G. Corneloup, J. Moysan, I.E. Magnin, BSCAN image segmentation by thresholding using cooccurrence matrix analysis, Pattern Recognition, in press.Google Scholar
- 4.M.C. Robini, I.E. Magnin, B. Lavayssiere, Wavelet packets based flaw detection in ultrasonic BSCAN images, International Conference on Quality Control by Artificial Vision, Creusot, France, 1995, p 37–47Google Scholar
- 5.J. Moysan, G. Corneloup, I.E. Magnin, P. Benoist, N. Chapuis, Détection et dimensionnement de défauts en imagerie ultrasonore, in Proc. du XIIIème Colloque sur le Traitement du Signal et des Images, Juan-Les-Pins, GRETSI, 1991, p 181–184.Google Scholar