Segmentation of radiographic images using fuzzy c-means algorithm

Xin Wang, Brian Stephen Wong

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)


Radiographic non-destructive testing is often used for detecting welding defects. Due to the degraded quality and the small size of the defects, X-ray films are sometimes difficult to interpret. The interpretation of such images is often affected by a human operator's subjectivity. Digital image processing techniques allow the interpretation to be automated. A key step in the automated interpretation process is the segmentation of indications from the background. In this paper, a segmentation method based on fuzzy c-means algorithm is applied to the radiographic image. In the proposed method, firstly top-hat, bottom-hat filter and adaptive wavelet thresholding are used to improve the quality of the radiographic image. Then, a fuzzy c-means algorithm is applied to segment the radiographic image. The experimental results show that the proposed method gives good performance for radiographic images.

Original languageEnglish
Pages (from-to)631-633
Number of pages3
JournalInsight: Non-Destructive Testing and Condition Monitoring
Issue number10
Publication statusPublished - Oct 2005
Externally publishedYes

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