A comparative evaluation of different segmentation techniques to detect flaws in weldments radiographically
In this paper, the concept of application of three segmentation techniques, ie morphological edge-based segmentation, region growing segmentation and multistage watershed segmentation, has been implemented on radiographic NDT images of weldments for the detection of flaws produced during the welding process. These methodologies are compared and concluded to be effective for the detection of all nine possible types of weld flaw (slag inclusion, worm hole, porosity, incomplete penetration, under cuts, cracks, lack of fusion, weaving fault and slag line) and feature extraction. After being successfully tested on more than 80 radiographic images obtained from EURECTEST, International Scientific Association Brussels, Belgium, 24 radiographs of ship welds provided by Technic Control Co, Poland, were used, obtained from Ioannis Valavanis, Greece. A comparative table showing the results is also presented in the paper. Many researchers used ANN, fuzzy logic, SVM and ANFIS novel methods to segment such types of image. Even though the results of these methods are impressive, they are time-consuming and require complex implementation. In contrast, the present methods are simple to implement and are optimised for time. The procedure to detect all types of flaw and feature extraction is implemented by a segmentation algorithm, which can overcome computer complexity problems. The experimental results show that our proposed method gives good performance on radiographic images.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
Document Type: Research Article
Publication date: October 1, 2011
More about this publication?
- Official Journal of The British Institute of Non-Destructive Testing - includes original research and devlopment papers, technical and scientific reviews and case studies in the fields of NDT and CM.
- Information for Authors
- Submit a Paper
- Subscribe to this Title
- Information for Advertisers
- Terms & Conditions
- Ingenta Connect is not responsible for the content or availability of external websites