Flaw detection improvement of digitised radiographs by morphological transformations

Amir Movafeghi, Mohammad Hossein Kargarnovin, Hamid Soltanian-Zadeh, M. Taheri, F. Ghasemi, B. Rokrok, K. Edalati, N. Rastkhah

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Radiographic inspection is one of the most appreciated techniques among non-destructive testing methods due to the production of a film which acts as a unique fingerprint record. Converting radiographs to a digital format and further digital image processing is the best method of enhancing the image quality and assisting the interpreter on his evaluation. In this research, different algorithms were used for image enhancement and radiograph interpretation in MATLAB environment. A graphical user interface (GUI) was created for implementation of different algorithms. Both spatial and frequency domains techniques were used for image enhancement. The main enhancement technique was a spatial technique based on morphological transformation (top-hat and bottom-hat transforms). The wavelet filtering was implemented as the frequency domain technique. A third technique, based on pseudo-colouring, was also used for a better comparison between different methods. Wavelet-based techniques are used very often nowadays. However, we show that wavelet applications are more complicated and a supervised and intelligent usage has to be carried out. A wisely established spatial technique can result in reasonably proper results. The diagnostic test reliability was carried out for the quantitative evaluation of the results with the help of industrial radiography interpreters. The obtained results indicated that the defect recognition probability can be increased effectively in both domains. However, it was concluded that better results can be achieved using a morphological method.

Original languageEnglish
Pages (from-to)625-630
Number of pages6
JournalInsight: Non-Destructive Testing and Condition Monitoring
Volume47
Issue number10
DOIs
Publication statusPublished - Oct 1 2005
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Metals and Alloys
  • Materials Chemistry

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  • Cite this

    Movafeghi, A., Kargarnovin, M. H., Soltanian-Zadeh, H., Taheri, M., Ghasemi, F., Rokrok, B., Edalati, K., & Rastkhah, N. (2005). Flaw detection improvement of digitised radiographs by morphological transformations. Insight: Non-Destructive Testing and Condition Monitoring, 47(10), 625-630. https://doi.org/10.1784/insi.2005.47.10.625