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This article presents a new algorithm for recognizing defects and discontinuities. It is a neural classification algorithm of the SVM class used for the vision system in the technological sequence. At the basis of the used method of Support Vector Machines  (SVM) lies the concept of decision-making space, which is divided by building boundaries separating objects with different class affiliation, that is, defects and discontinuities.
The Support Vector Machines method is supposed to perform classification tasks by constructing in a multidimensional space hyperplane separating cases belonging to different classes.