Abstract
A method of image morphology in detecting and extracting the initial welding position during the autonomous welding process is described. During the process, firstly visual sensing technology is used to capture the straight seam image, and secondly the image edges are detected by morphological corrosion edge detection algorithm, with which can retain the critical information while filter other interferences effectively at the same time. Then morphological processing algorithm is used to conduct the direction of filter by selecting the multidirectional linear structuring elements and finally get the initial weld position point coordinates with the Hough transform. The algorithm is simple, rapid, self-adaptability with high accuracy for interferences except long lines so as to accomplish the entire process of detecting the initial welding position. It can meet the practical demands of automatic guidance for robotic welding.
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References
Tarn T J, Chen S B, Zhou C J. Robotic welding, intelligence and automation [M]. Berlin: Springer-Verlag, 2010.
Zhu Z Y, Lin T, Piao Y J, et al. Recognition of the initial position of weld based on the image pattern match technology for welding robot [J]. International Journal of Advanced Manufacturing Technology, 2005, 26: 784–788.
Mukhopashyay S, Chanda B. An edge preserving noise smoothing technique using multi-scale morphology [J]. Signal Processing, 2002, 82(4): 527–544.
Zhang L J, Xu J W, Yang J H, et al. Multiscale morphology analysis and its application to fault diagnosis [J]. Mechanical Systems and Signal Processing, 2008, 22: 597–610.
Verdú-Monedero R, Angulo J. Spatially-variant directional mathematical morphology operators based on a diffused average squared gradient field [J]. Lecture Notes in Computer Science, 2008, 5259: 542–553.
Li T G, Wang S P, Zhao N. Gray-scale edge detection for gastric tumor pathologic cell images by morphological analysis [J]. Computers in Biology and Medicine, 2009, 39: 947–952.
Gonzalez R C, Woods R E, Eddins S L. Digital image processing using MATLAB [M]. Beijing: Publishing House of Electronics Industry, 2004.
Verdú-Monedero R, Angulo J, Serra J. Spatially-variant anisotropic morphological filters driven by gradient fields [J]. Lecture Notes in Computer Science, 2009, 5720: 115–125.
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Wei, Sc., Wang, J., Lin, T. et al. Application of image morphology in detecting and extracting the initial welding position. J. Shanghai Jiaotong Univ. (Sci.) 17, 323–326 (2012). https://doi.org/10.1007/s12204-012-1278-9
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DOI: https://doi.org/10.1007/s12204-012-1278-9