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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PH2NFL
Repositorysid.inpe.br/sibgrapi/2017/08.29.01.15
Last Update2017:08.29.01.15.25 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.29.01.15.25
Metadata Last Update2022:05.18.22.18.23 (UTC) administrator
Citation KeyMacariniWebe:2017:QuCoSy
TitleQuality Control System for Ceramic Tiles using Segmentation-based Fractal Texture Analysis and SVM
FormatOn-line
Year2017
Access Date2025, July 14
Number of Files1
Size429 KiB
2. Context
Author1 Macarini, Luiz Antonio
2 Weber, Tiago Oliveira
Affiliation1 Universidade Federal de Santa Catarina
2 Universidade Federal de Santa Catarina
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
e-Mail Addressluiz.buschetto@grad.ufsc.br
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeIndustry Application Paper
History (UTC)2017-08-29 01:15:25 :: luiz.buschetto@grad.ufsc.br -> administrator ::
2022-05-18 22:18:23 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsImage Processing
Machine Learning
SFTA
Ceramic Tiles
Defect Detection
AbstractThe ceramic industry has a highly automated production system. The quality control, however, is still performed by humans, which limits its speed and precision. This work proposes a complete verification system for ceramic tiles based on image processing and machine learning. The system has four steps: image acquisition, pre-processing, feature extraction and classification. The feature extraction step uses Segmentation-based Fractal Texture Analysis (SFTA). A Support Vector Machine is employed to classify the ceramic tiles. The system is implemented using OpenCV libraries. In total, 783 ceramic tiles were used, being 80% for training and 20% to testing. The present work had reached the proposed objectives, both in processing time and accuracy, achieving 98.68% of detection rate.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2017 > Quality Control System...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PH2NFL
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PH2NFL
Languageen
Target FileSIBGRAPI_Luiz_Tiago.pdf
User Groupluiz.buschetto@grad.ufsc.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 40
sid.inpe.br/banon/2001/03.30.15.38.24 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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