31 July 2006 The research of defects detection and segmentation for weld radiographic inspection
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Proceedings Volume 5960, Visual Communications and Image Processing 2005; 59602M (2006) https://doi.org/10.1117/12.631583
Event: Visual Communications and Image Processing 2005, 2005, Beijing, China
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.
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Xiao-guang Zhang, Yu Li, Xuedong Lin, Mingqin Liu, Ji-hua Xu, "The research of defects detection and segmentation for weld radiographic inspection", Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59602M (31 July 2006); doi: 10.1117/12.631583; https://doi.org/10.1117/12.631583
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