Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3MCEPSH
Repositorysid.inpe.br/sibgrapi/2016/09.02.21.25
Last Update2016:09.02.21.35.23 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2016/09.02.21.25.35
Metadata Last Update2022:05.18.22.21.09 (UTC) administrator
Citation KeyRochaMeneOliv:2016:DeAuMi
TitleDetecção Automática de Microcomponentes SMT Ausentes em Placas de Circuito Impresso
FormatOn-line
Year2016
Access Date2024, Sep. 17
Number of Files1
Size2778 KiB
2. Context
Author1 Rocha, Cleandro de Souza
2 Menezes, Mathias Afonso Guedes de
3 Oliveira, Felipe Gomes de
Affiliation1 Federal University of Amazoas
2 Federal University of Amazonas
3 Federal University of Amazonas
EditorAliaga, Daniel G.
Davis, Larry S.
Farias, Ricardo C.
Fernandes, Leandro A. F.
Gibson, Stuart J.
Giraldi, Gilson A.
Gois, João Paulo
Maciel, Anderson
Menotti, David
Miranda, Paulo A. V.
Musse, Soraia
Namikawa, Laercio
Pamplona, Mauricio
Papa, João Paulo
Santos, Jefersson dos
Schwartz, William Robson
Thomaz, Carlos E.
e-Mail Addressfelipe.inad@gmail.com
Conference NameConference on Graphics, Patterns and Images, 29 (SIBGRAPI)
Conference LocationSão José dos Campos, SP, Brazil
Date4-7 Oct. 2016
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeIndustry Application Paper
History (UTC)2016-09-02 21:35:23 :: felipe.inad@gmail.com -> administrator :: 2016
2022-05-18 22:21:09 :: administrator -> :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsVisão de Máquina
Aprendizado de Máquina
Inspeção Industrial
Controle de Qualidade
AbstractThis work presents a visual inspection approach to detect absence/presence of surface mount components (SMC) on printed circuit boards (PCB). We propose a methodology based on the combination of Machine Vision and Machine Learning to detect component absence, with more quality and precision, using noised digital images acquired directly from PCB industrial production line. The applicability of method was tested for automatic visual inspection in motherboards, where the demand of these components is high. The results obtained demonstrates the robustness of our methodology in images with high levels of gaussian and salt and pepper noise, obtaining 97.25% of hit rate.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2016 > Detecção Automática de...
doc Directory Contentaccess
source Directory Content
Sibgrapi2016_CameraReady.pdf 02/09/2016 18:25 2.7 MiB
agreement Directory Content
agreement.html 02/09/2016 18:25 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3MCEPSH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3MCEPSH
Languagept
Target FileSibgrapi2016_CameraReady.pdf
User Groupfelipe.inad@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3M2D4LP
Citing Item Listsid.inpe.br/sibgrapi/2016/07.02.23.50 21
sid.inpe.br/banon/2001/03.30.15.38.24 4
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


Close