Automatic Detection of Weld Defects Based on Hough Transform

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 localize 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. In this article, a robust and automatic method is presented to detect linear defect from the original image without selection of ROI based on canny detector and a modified ‘Hough Transform’ technique. This task can be subdivided into the following steps: firstly, preprocessing step with Gaussian filter and contrast stretching; secondly, segmentation technique is used to isolate weld region from background and non-weld using Adaptative Thresholding and to extract edges; thirdly, detection, location of linear defect and limiting the welding area by Hough Transform. The experimental results show that our proposed method gives good performance for industrial radiographic images.