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Detection of line weld defects based on multiple thresholds and support vector machine
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Indexed by:期刊论文

Date of Publication:2008-10-01

Journal:NDT & E INTERNATIONAL

Included Journals:SCIE、EI、Scopus

Volume:41

Issue:7

Page Number:517-524

ISSN No.:0963-8695

Key Words:weld defect detection; X-ray image; support vector machine (SVM); Hough transform

Abstract:Because X-ray images of weld contain uncertain noise and also the defects inside them have low contrast to their background, it is difficult to detect weld defects of X-ray images. The goal of this paper is to locate and segment the line defects in X-ray images. Firstly, we present an approach to extract features of X-ray images with multiple thresholds. Then, use the support vector machine (SVM) technique to classify the defect and non-defect features to obtain a coarse defect region. Furthermore, perform the Hough transform to remove the noisy pixels in the coarse defect region. Then the defect is located and segmented. The experimental results show that the proposed approach is effective and feasible to segment and locate defects in noisy and low contrasted X-ray images of weld. (c) 2008 Elsevier Ltd. All rights reserved.

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Gender:Female

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:信息与通信工程学院

Business Address:海山楼A420

Contact Information:lslwf@dlut.edu.cn

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