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Proceedings Paper

The research of defects detection and segmentation for weld radiographic inspection
Author(s): Xiao-guang Zhang; Yu Li; Xuedong Lin; Mingqin Liu; Ji-hua Xu
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Paper Abstract

Both digital radioscopy and radiographic testing rely on human experts to perform manual interpretation of images, and the recognition of welding defects demands the inspector's vast experience. With computer detect defects in a weld image; many countries have been made seeking the development of automatic system of inspection of welding defects. Defects were detected and segmented is key step for automatic recognition from welding image. This paper presents an algorithm of defects detection and segmentation for weld radiographic inspection which is based on wavelet analysis. The detection algorithm based on waveform analysis classifies weld defects as trough-anomaly, peak-anomaly and slanttrough- anomaly three types firstly. Aiming at to trough-anomaly and slant-trough-anomaly, weld defects inside them can be classified as crack and non-crack according to the width of two peaks in following. Different segmentation algorithms are adopted to these two types defects sequently. The experimental results show that the algorithm is very effective.

Paper Details

Date Published: 31 July 2006
PDF: 8 pages
Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59602M (31 July 2006); doi: 10.1117/12.631583
Show Author Affiliations
Xiao-guang Zhang, China Univ. of Mining and Technology (China)
Nanjing Univ. (China)
Yu Li, China Univ. of Mining and Technology (China)
Xuedong Lin, China Univ. of Mining and Technology (China)
Mingqin Liu, China Univ. of Mining and Technology (China)
Ji-hua Xu, Nanjing Univ. (China)


Published in SPIE Proceedings Vol. 5960:
Visual Communications and Image Processing 2005
Shipeng Li; Fernando Pereira; Heung-Yeung Shum; Andrew G. Tescher, Editor(s)

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