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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3PF6BJ8
Repositorysid.inpe.br/sibgrapi/2017/08.17.13.40
Last Update2017:08.17.13.40.25 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2017/08.17.13.40.25
Metadata Last Update2022:06.14.00.08.44 (UTC) administrator
DOI10.1109/SIBGRAPI.2017.18
Citation KeyOliveiraNass:2017:DeMoPr
TitleDetecting modifications in printed circuit boards from fuel pump controllers
FormatOn-line
Year2017
Access Date2024, May 02
Number of Files1
Size4683 KiB
2. Context
Author1 Oliveira, Thomas Jose Mazon de
2 Marco Aurelio Wehrmeister
3 Nassu, Bogdan Tomoyuki
Affiliation1 Federal University of Technology - Parana
2 Federal University of Technology - Parana
3 Federal University of Technology - Parana
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 Addressthomasoliveira@alunos.utfpr.edu.br
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ, Brazil
Date17-20 Oct. 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-17 13:40:25 :: thomasoliveira@alunos.utfpr.edu.br -> administrator ::
2022-06-14 00:08:44 :: administrator -> :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsImage-based detection of modifications in printed circuit boards
Fraud detection in fuel pumps
Computer vision
image registration
machine learning
Points of interest
AbstractFrauds involving illegal modifications to the printedcircuit boards from fuel pump controllers are a serious problem,which not only harms customers, but also connects to othercrimes, such as money laundering and tax evasion. The currentstate-of-practice for inspecting these boards is a visual analysisperformed by a human. In this paper, we introduce an image-based approach that can provide support to the human inspectorby automatically detecting suspicious regions in the boards.The proposed approach aligns a photograph of the inspectedboard to a reference view, partitions the image in sub-regions,extracts features using a variation of the popular Scale-InvariantFeature Transform, classifies the features against previouslytrained Support Vector Machines, and integrates the results forpresentation. In experiments performed on a dataset containing649 images from a board, with and without modifications, ourapproach achieved a precision of 0.7739, a recall of 0.9434, andanF-measure 0.8503. These results indicate that our approachcan effectively identify suspicious regions, providing invaluablehelp to the human inspector.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2017 > Detecting modifications in...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Detecting modifications in...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3PF6BJ8
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PF6BJ8
Languageen
Target FileSibGrapi.pdf
User Groupthomasoliveira@alunos.utfpr.edu.br
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PKCC58
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2017/09.12.13.04 9
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination 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 volume


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