Classification of welding defects in radiographic images
- Authors: Moghaddam A.A.1, Rangarajan L.1
-
Affiliations:
- Department of Studies in Computer Science
- Issue: Vol 26, No 1 (2016)
- Pages: 54-60
- Section: Applied Problems
- URL: https://journals.rcsi.science/1054-6618/article/view/194480
- DOI: https://doi.org/10.1134/S1054661815040021
- ID: 194480
Cite item
Abstract
Welding defects detection and classification is very important to guarantee the welding quality. Over the last 30 years, there has been a large amount of research attempting to develop an automatic (or semiautomatic) system for the detection and classification of weld defects in continuous welds using radiography. In this paper, we describe an automatic system for classification of welding defects from radiographic images and compare with KNN and SVM classifiers. We classify and recognize the linear defects such as lack of penetrations, incomplete fusion and external undercut. Experimental results have shown the classification method is useful for the lengthy defects and obtained through our method is better than the two classifiers methods.
About the authors
A. Azari Moghaddam
Department of Studies in Computer Science
Author for correspondence.
Email: arazarim@gmail.com
Iran, Islamic Republic of, Royan, 46157 97983
L. Rangarajan
Department of Studies in Computer Science
Email: arazarim@gmail.com
India, Mysore, 570006
Supplementary files
