Discontinuities detection in welded joints based on inverse surface thresholding

被引:17
作者
Yazid, Haniza [1 ,2 ]
Arof, H. [1 ]
Yazid, Hafizal [3 ]
Ahmad, Sahrim [3 ]
Mohamed, A. A. [3 ]
Ahmad, F. [4 ]
机构
[1] Univ Malaya, Fac Engn, Dept Elect Engn, Kuala Lumpur 50603, Malaysia
[2] Univ Malaysia Perlis, Sch Mechatron Engn, Arau 02600, Perlis, Malaysia
[3] Agensi Nuklear Malaysia, Ind Technol Div, Bangi 43000, Kajang, Malaysia
[4] UTMSPACE, Dept Elect Engn, Kuala Lumpur 54100, Malaysia
关键词
Non-destructive testing; Welded joints; Inverse surface thresholding; Fuzzy c means clustering; RADIOGRAPHIC NDT SYSTEM; IMAGE SEGMENTATION; DEFECT DETECTION; WELDING DEFECTS; INSPECTION; EXTRACTION;
D O I
10.1016/j.ndteint.2011.06.002
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Automated detection of welding defects in radiographic images becomes nontrivial when uneven illumination, contrast and noise are present. In this paper, a new approach using surface thresholding method is proposed to detect defects in radiographic images of welding joints. In the first stage, several image processing techniques namely fuzzy c means clustering, region filling, mean filtering, edge detection, Otsu thresholding, and morphological operations method are utilized to locate the area where defects might exist. This is followed by the construction of the inverse thresholding surface and its implementation to locate defects in the identified area. The proposed method was tested on 60 radiographic images and it obtained 94.6% sensitivity. Its performance is compared to that of the watershed segmentation, which obtained 69.6%. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:563 / 570
页数:8
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