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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/49LJ6AH
Repositorysid.inpe.br/sibgrapi/2023/08.18.23.49
Last Update2023:08.18.23.49.47 (UTC) lucianebaldassari@gmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2023/08.18.23.49.47
Metadata Last Update2024:02.17.04.05.19 (UTC) administrator
DOI10.1109/SIBGRAPI59091.2023.10347152
Citation KeySoaresEMMMPJB:2023:SeReMa
TitleSegmentation and Removal of Markings in Metal Inspection Images
FormatOn-line
Year2023
Access Date2024, May 05
Number of Files1
Size5573 KiB
2. Context
Author1 Soares, Luciane Baldassari
2 Evangelista, Eduardo
3 Maurente, Vinicius
4 Machado, Matheus
5 Maurell, Igor
6 Pias, Marcelo
7 Jr, Paulo Drews
8 Botelho, Silvia
Affiliation1 Universidade Federal do Rio Grande - FURG
2 Universidade Federal do Rio Grande - FURG
3 Universidade Federal do Rio Grande - FURG
4 Universidade Federal do Rio Grande - FURG
5 Universidade Federal do Rio Grande - FURG
6 Universidade Federal do Rio Grande - FURG
7 Universidade Federal do Rio Grande - FURG
8 Universidade Federal do Rio Grande - FURG
EditorClua, Esteban Walter Gonzalez
Körting, Thales Sehn
Paulovich, Fernando Vieira
Feris, Rogerio
e-Mail Addresslucianebaldassari@gmail.com
Conference NameConference on Graphics, Patterns and Images, 36 (SIBGRAPI)
Conference LocationRio Grande, RS
DateNov. 06-09, 2023
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2023-08-18 23:49:47 :: lucianebaldassari@gmail.com -> administrator ::
2024-02-17 04:05:19 :: administrator -> lucianebaldassari@gmail.com :: 2023
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsInpainting
segmentation
inspection images
AbstractThe inspection process of metallic surfaces, especially FPSO tanks, is still heavily reliant on manual methods, requiring long production downtime and posing health risks to inspectors. Automating this analysis step will provide significant benefits to the management of these vessels' integrity, reducing expenses, downtime, and, most importantly, the exposure time of employees to hazards associated with inspection activities. During manual inspections, inspectors make annotations using paint, typically in white and yellow colors, directly on the tank walls, hindering the automation of the inspection process as it complicates the segmentation and identification of potential flaws on the tank wall using techniques such as neural network models. Recognizing this problem, this work presents a proposal for the identification and segmentation of these markings by segmenting them in the images, followed by the removal of the segmented markings using image texture-filling techniques.
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/49LJ6AH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/49LJ6AH
Languageen
Target FileSOARES-101.pdf
User Grouplucianebaldassari@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
7. Description control
e-Mail (login)lucianebaldassari@gmail.com
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