Abstract
Weld defect detection is an important application in the field of non-destructive testing (NDT). These defects are mainly due to manufacturing errors or welding processes. In this context, image processing especially segmentation is proposed to detect and localise efficiently different types of defects. It is a challenging task since radiographic images have deficient contrast, poor quality and uneven illumination caused by the inspection techniques. The usual segmentation technique uses a region of interest (ROI) from the original image. A robust and automatic method is presented to detect two major defect types from mono or multi-weld defects images. So, pre-processing tools are applied based on Gaussian filter and contrast stretching then segmentation too is performed based on Gabor filter, binarisation and Canny detector to extract edges and finally detection and location of multi-weld defects with a modified 'Hough transform' technique. The experimental results show that our proposed method gives good performance.