Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/34191
Title: Discontinuities detection in welded joints based on inverse surface thresholding
Authors: Haniza, Yazid, Dr.
Hamzah, Arof, Dr.
Hafizal, Yazid
Sahrim, Ahmad
Abdul Aziz, Mohamed
Fauzan, Ahmad
haniza.yazid@gmail.com
Keywords: Fuzzy c means clustering
Inverse surface thresholding
Non-destructive testing
Welded joints
Issue Date: 2011
Publisher: Elsevier Ltd.
Citation: NDT and E International, vol. 44(7), 2011, pages 563-570
Abstract: 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%.
Description: Link to publisher's homepage at http://www.sciencedirect.com/
URI: http://www.sciencedirect.com/science/article/pii/S0963869511000752
http://dspace.unimap.edu.my:80/dspace/handle/123456789/34191
ISSN: 0963-8695
Appears in Collections:Haniza Yazid, Dr.

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