Fourth-order B-spline wavelet multiscale local modulus maxima for edge detection in identification of pipeline fault

Peixin Yuan; Jun Tan; Jiahui Cong

doi:10.1117/12.850586

14 April 2010 Fourth-order B-spline wavelet multiscale local modulus maxima for edge detection in identification of pipeline fault

Peixin Yuan, Jun Tan, Jiahui Cong

Author Affiliations +

Proceedings Volume 7522, Fourth International Conference on Experimental Mechanics; 75226P (2010) https://doi.org/10.1117/12.850586
Event: Fourth International Conference on Experimental Mechanics, 2009, Singapore, Singapore

Abstract

In this paper, for the actual in-service pipeline detection, an edge detection method based on fourth-order B-spline wavelet multi-scale local modulus maxima is proposed. We extract defect edge using wavelet maximum algorithm, select fine length, invariant moment, gray scale energy and so on, several key characteristic parameters that are good for defect identification, and use BP neural network of single-output form for pattern recognition. By this method we complete the classification of the pipe weld joints and corrosion defects, and quantitative identification of corrosion defects.

Citation Download Citation

Peixin Yuan, Jun Tan, and Jiahui Cong "Fourth-order B-spline wavelet multiscale local modulus maxima for edge detection in identification of pipeline fault", Proc. SPIE 7522, Fourth International Conference on Experimental Mechanics, 75226P (14 April 2010); https://doi.org/10.1117/12.850586

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