Incomplete Penetration Type Flaws Detection in Weldments Using Morphological Image Processing Techniques
DOI:
https://doi.org/10.18486/ijcsnt/5.2.069Keywords:
Radiographic Images, Flaw Detection, Edge Detection, Dilation, ErosionAbstract
It is necessary to detect suspected defect regions in the radiographic weld images to find the flaw and its causative factors. This requires processing of radiographic images by a suitable approach. This paper presents an image processing approach to process incomplete penetration type flaws in radiographic images of the weld specimens considering morphological aspects of the image. In the present approach, radiographic weld image is processed to get the image with good contrast and reduced noise using image enhancement techniques like histogram equalization and noise filtering. This is followed by an effective edge detector such as Canny operator to find the edges of flaws, which are further used to segment the image to fixed the boundaries. The boundaries are fixed using morphological image processing approach i.e. dilating few similar boundaries and eroding some irrelevant boundaries decided on the basis of pixel characteristics. The incomplete penetration type flaws are clearly identifiable in the finally processed image, which is obtained by superimposing the segmented image over the original enhanced image.
References
Nockeman C., Heidt H. and Tomsen N. "Reliability in NDT: ROC Study of Radiographic Weld Inspection." NDT & E International, 1991; 24(5): 235–245. DOI: https://doi.org/10.1016/0963-8695(91)90372-A
Hayes C. "ABC's of Nondestructive Weld Examination." Welding Journal, 1997; 76(5): 46–51.
Li Y. "Optimizing Radiographic NDT Techniques for Welds." NDT & E International, 1994; 27(1): 15–20. DOI: https://doi.org/10.1016/0963-8695(94)90005-1
Halmshaw R. "Flaw Sensitivity in Relation to Standard for Film Radiography." Materials Evaluation, 1992: 678–683.
Kaftandjian, Joly A., Odievre T. et al. "Automatic Detection and Characterization of Aluminum Weld Defects: Comparison Between Radiography, Radioscopy and Human Interpretation." In: 7th ECNDT, Vol. 3, pp. 1–7.
Vamos G., Lovanyi I., Nagy A. et al. "Flaw Detection in Metallic Fusion Welds on X-Ray Images Using Bayesian Networks." In: Proceedings of the 1st Hungarian Conference, pp. 118–123.
Grieve D. J. Welding Defects. www.tech.plym.ac.uk/sme/strc201/wdefects.htm.
Laggoune H. and Gouton S. P. "Dimensional Analysis of the Welding Zone." In: Proceedings of the 22nd International Conference on Information Technology Interfaces, pp. 451–456.
Daillant G., Micollet D. and Paindavoine M. "Defect in a Weld: A Complete Radiographic Processing Line." In: Proceedings of the 22nd IEEE IECON International Conference on Industrial Electronics, Control, and Instrumentation, pp. 719–724. DOI: https://doi.org/10.1109/IECON.1996.565966
Canny J. "A Computational Approach to Edge Detection." IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986; 8(6). DOI: https://doi.org/10.1109/TPAMI.1986.4767851
Gonzalez R. C. and Woods R. E. Digital Image Processing. 2nd ed. Pearson Education Asia, 2002.
Sonka M., Hlavac V. and Boyle R. Image Processing, Analysis, and Machine Vision. 2nd ed., 2003.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Alaknanda Ashok
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
