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Methods of automated image processing in solving problems of magnetic defectoscopy
Korobeinikov Anatolii Grigor'evich

Doctor of Technical Science

Deputy Director of Science, St. Petersburg Branch of the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation of the Russian Academy of Sciences

199034, Russia, Saint Petersburg, liniya Mendeleevskaya, 1
Aleksanin Sergei Andreevich

graduate student, St. Petersburg State University of Information Technologies, Mechanics and Optics

197101, Russia, Saint Petersburg, Kronverkskii Prospekt, 49
Abstract. The subject of study in this paper is developed automated method of selecting of procedures of processing images gathered for the magnetic defectoscopy.  The methods based on the analysis of magnetic fields scattering near the defects after the magnetization of these products are used to detect various defects, such as cracks, in the surface layers of steel parts. In areas where there is a discontinuity, the change of the magnetic flux is present. This effect is the basis of almost all existing methods of magnetic defectoscopy. One of the most known methods of magnetic defectoscopy of method is a magnetic powder: the surface of the magnetized part is covered with magnetic powder (dry method) or magnetic slurry (wet method). When using fluorescent powders and suspensions, the images of the studied details show visible defects significantly better. Therefore, it is possible to automate the processing of images. The paper presents an automated procedure for selecting methods of image processing. The authors give an example of processing image of steel parts for detecting defects using the luminous lines that appeared after applying the magnetic slurry. The study uses the methods of the theory of image processing. These are mainly extraction methods for defining boundaries of objects and morphological image processing. The main result of an automated method is the opportunity to obtain expert information on the basis of which it is possible to make a conclusion about the presence of defects in the test product. In the example given in the article authors show that the lines are continuous and have no sharp change of direction. Therefore, the conclusion about the absence of discontinuities (defects) in the product is made. In addition, authors point out that the binary image can be inverted at the request of the researcher.
Keywords: smoothed image, contrast adjustment, edge detection, morphological filtering, image enhancement, image processing, magnetic particle inspection, deblurring, blind deconvolution, convolution
DOI: 10.7256/2306-4196.2015.4.16320
Article was received: 11-09-2015

Review date: 12-09-2015

Publish date: 25-09-2015

This article written in Russian. You can find full text of article in Russian here.

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