Application of the Image Segmentation Techniques for the Problems of Surface Defects Detection of Welds

Applications of images segmentation techniques are analyzed applied to the problem of surface defect detection. The multi-stage procedure of the surface defect detection is considered. Efficiency of the proposed algorithms of digital image processing is proved out by the test results using software system of surface defects detection on the images of welded connections of ring joints of large diameter pipes.

References

[1] Perkovskiy R.A., Gavrilov A.I., Shirankov A.F., Rogov A.B., Nadymov N.P Installation for the hard stamp’s reading from tubing. Defektoskopija [Rus. J. Nondestr. Test.], 2003, no. 9, pp. 81-83 (in Russ.).

[2] Getskin O.B., Vyshemirskiy E.M., Shipilov A.V., Poloskov S.I. Experience in the development and application of modern domestic technologies and equipment for automatic orbital welding of trunk pipelines. Svarka i Diagnostika [Welding and Diagnostics], 2010, no. 6, pp. 51-57 (in Russ.).

[3] Gonzalez R.C., Woods R.E. Digital image processing. Prentice Hall, 2002. 813 p. (Russ. Ed.: Gonzales R., Vuds R. Cifrovaja obrabotka izobrazhenij. Moscow, Tehnosfera Publ., 2006. 1072 p.).

[4] Mironov B.M., Malov A.N. Segmentation of images by cluster’s method and by the algorithm of random jump: comparative analysis. Komp. Optika [Comp. Opt.], 2010, vol. 34, no. 1, pp. 132-137 (in Russ.).

[5] Shapiro L., Stockman G. Computer vision. Prentice Hall, 2001. 608 p. (Russ. ed.: Shapiro L., Stokman Dzh. Komp’juternoe zrenie. Moscow, BINOM. Laboratorija znanij Publ., 2006. 752 p.).

[6] Gladkov E.A., Perkovskiy R.A., Getskin B.L., Gavrilov A.I., Brodjagin V.N. The automated complex for multi-layer welding of circular seams of pipes of main pipelines with the means of adaptation and forecasting of quality welding. Nauka i tehn. v gaz. prom. [Sci. & Techn. in the Gas Ind. J.], 2009, no. 4, pp. 77-86 (in Russ.).

[7] Gladkov E.A., Maloletkov A.V., Gavrilov A.I., Perkovskiy R.A. Methodical aspects of the use of neural network models to predict the quality of fusion welding. Svarka i Diagnostika [Welding and Diagnostics], 2008, no. 3, pp. 2-7 (in Russ.).

[8] Gladkov E.A., Gavrilov A.I. Simulation modeling of laser welding deep penetration using neural network models. Svarka i Diagnostika, 2009, no. 1, pp. 9-11 (in Russ.).

[9] Aleshin N.P., Gladkov E.A., Perkovskiy R.A., Gavrilov A.I., Brodjagin V.N. Mikroprocessornyj kompleks monitoringa i upravlenija processom svarki kol’cevyh stykov trub [Microprocessor complex monitoring and process control welding of circular pipe joints]. Patent RF, no. 121765, 2011.

[10] Aleshin N.P., Gladkov E.A., Gavrilov A.I., Perkovskiy R.A., Rahmatullin T.A. Implementation of adaptive technology of welding of circular joints of pipelines. Svarka i Diagnostika [Welding and Diagnostics], 2011, no. 5, pp. 48-53 (in Russ.).

[11] Fisenko V.T., Fisenko T.Ju. Komp’juternaja obrabotka i raspoznavanie izobrazhenij [Computer processing and image recognition]. SPb., SPbGU ITMO Publ., 2008. 192 p.

[12] Gladkov E.A., Gavrilov A.I., Maloletkov A.V. Dynamic nonlinear model technical process of laser welding with deep penetration. Svarochnoe proizvodstvo [Welding production], 2001, no. 12. pp. 17-24 (in Russ.).

[13] Jahne B. Digital Image Processing. 6th Ed. Springer Berlin Heidelberg New York, 2005. 654 p. (Russ. Ed.: Jane B. Cifrovaja obrabotka izobrazhenij. Moscow, Tehnosfera Publ., 2007. 584 p.).

[14] Gruzman I.S., Kirichuk VS., Kosyh V.P., Peretjagin G.I., Spektor A.A. Cifrovaja obrabotka izobrazhenij v informacionnyh sistemah [Digital image processing in information systems]. Novosibirsk, NGTU Publ., 2003. 352 p. (in Russ.).