Automatic label removal from digitized weld radiographs

This paper presents a methodology to remove labels automatically from digitized weld radiographs as part of the automatic weld defect detection process. An algorithm was developed to detect and remove labels printed onto weld radiographs before weld extraction algorithm or defect detection algorithm...

Full description

Saved in:
Bibliographic Details
Main Authors: Soo, Say Leong, Ratnam, Mani Maran, Samad, Zahurin, Khalid, Mohd. Ashhar
Format: Article
Language:English
Published: Penerbit UTM Press 2007
Subjects:
Online Access:http://eprints.utm.my/id/eprint/6200/1/JTDIS47D01.pdf
http://eprints.utm.my/id/eprint/6200/
http://www.penerbit.utm.my/onlinejournal/47/D/JTDIS47D01.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.6200
record_format eprints
spelling my.utm.62002017-11-01T04:17:25Z http://eprints.utm.my/id/eprint/6200/ Automatic label removal from digitized weld radiographs Soo, Say Leong Ratnam, Mani Maran Samad, Zahurin Khalid, Mohd. Ashhar TJ Mechanical engineering and machinery This paper presents a methodology to remove labels automatically from digitized weld radiographs as part of the automatic weld defect detection process. An algorithm was developed to detect and remove labels printed onto weld radiographs before weld extraction algorithm or defect detection algorithm is applied. Normality test was used to determine if the intensity profile parallel to the weld contains label pixels. Thresholding followed by region filling operations were carried out to remove the labels. The algorithm was tested on 50 weld radiographs with labels and the labels on 90% of these images were successfully removed. Penerbit UTM Press 2007-12 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/6200/1/JTDIS47D01.pdf Soo, Say Leong and Ratnam, Mani Maran and Samad, Zahurin and Khalid, Mohd. Ashhar (2007) Automatic label removal from digitized weld radiographs. Jurnal Teknologi D . pp. 1-14. ISSN 0127-9696 http://www.penerbit.utm.my/onlinejournal/47/D/JTDIS47D01.pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Soo, Say Leong
Ratnam, Mani Maran
Samad, Zahurin
Khalid, Mohd. Ashhar
Automatic label removal from digitized weld radiographs
description This paper presents a methodology to remove labels automatically from digitized weld radiographs as part of the automatic weld defect detection process. An algorithm was developed to detect and remove labels printed onto weld radiographs before weld extraction algorithm or defect detection algorithm is applied. Normality test was used to determine if the intensity profile parallel to the weld contains label pixels. Thresholding followed by region filling operations were carried out to remove the labels. The algorithm was tested on 50 weld radiographs with labels and the labels on 90% of these images were successfully removed.
format Article
author Soo, Say Leong
Ratnam, Mani Maran
Samad, Zahurin
Khalid, Mohd. Ashhar
author_facet Soo, Say Leong
Ratnam, Mani Maran
Samad, Zahurin
Khalid, Mohd. Ashhar
author_sort Soo, Say Leong
title Automatic label removal from digitized weld radiographs
title_short Automatic label removal from digitized weld radiographs
title_full Automatic label removal from digitized weld radiographs
title_fullStr Automatic label removal from digitized weld radiographs
title_full_unstemmed Automatic label removal from digitized weld radiographs
title_sort automatic label removal from digitized weld radiographs
publisher Penerbit UTM Press
publishDate 2007
url http://eprints.utm.my/id/eprint/6200/1/JTDIS47D01.pdf
http://eprints.utm.my/id/eprint/6200/
http://www.penerbit.utm.my/onlinejournal/47/D/JTDIS47D01.pdf
_version_ 1643644500576305152
score 13.223943