Multi-weld defects detection based on Gabor filter, Hough transform
by Chiraz Ajmi; Sabra Elferchichi; Juan Zapata; Abderrahmen Zaafouri; Kaouther Laabidi
International Journal of Modelling, Identification and Control (IJMIC), Vol. 38, No. 3/4, 2021

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.

Online publication date: Mon, 13-Jun-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com