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Proceedings Paper

Keyhole image processing based on the wavelet transform in the VPPA welding process
Author(s): Zhonghua Liu; Qilong Wang
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Paper Abstract

In order to realize the feedback control for variable polarity plasma arc weld formation in the weld process, the feature geometrical size of the keyhole must be extracted. A multiscale edge detection based on the wavelet transform is equivalent to finding the local maxima of a wavelet transform. With the properties of multiscale edge through the wavelet theory, the edge points were detected by getting the maximum modulus of the gradient vector in the direction towards which the gradient vector points in the image plane. The edge points with a large module value correspond to the sharper intensity variation of the image. At coarse scales, the maxima of modules have different positions than at the fine scales and only detected the sharp edge. At fine scale, there are many maxima create by the image noise. We must integrate this multiscale information to look for the best scale where the edges are well discriminated from noises. At last, a new method of peak analysis for threshold selection is proved. It is based on the wavelet transform which provides a multiscale analysis of the information of the histogram. We how that the detection of the zero-crossing or the local extrema of a wavelet transform of the histogram gives a compete characterization of het peaks in the histogram. Many experiments show these ways are effective for the keyhole image to get the geometry parameters of the keyhole in the real-time image processing.

Paper Details

Date Published: 5 April 2000
PDF: 8 pages
Proc. SPIE 4056, Wavelet Applications VII, (5 April 2000); doi: 10.1117/12.381704
Show Author Affiliations
Zhonghua Liu, Harbin Institute of Technology (China)
Qilong Wang, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 4056:
Wavelet Applications VII
Harold H. Szu; Martin Vetterli; William J. Campbell; James R. Buss, Editor(s)

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