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Information System for Automation of Counterfeited Documents Images Correlation

dc.contributor.authorVieira, Rafael
dc.contributor.authorSilva, Catarina
dc.contributor.authorAntunes, Mário
dc.contributor.authorAssis, Ana
dc.date.accessioned2025-06-17T09:01:23Z
dc.date.available2025-06-17T09:01:23Z
dc.date.issued2016
dc.description.abstractForgery detection of official documents is a continuous challenge encountered by documents’ forensic experts. Among the most common counterfeited documents we may find citizen cards, passports and driving licenses. Forgers are increasingly resorting to more sophisticated techniques to produce fake documents, trying to deceive criminal polices and hamper their work. Having an updated past counterfeited documents image catalogue enables forensic experts to determine if a similar technique or material was already used to forge a document. Thus, through the modus operandi characterization is possible to obtain more information about the source of the counterfeited document. In this paper we present an information system to manage counterfeited documents images that includes a two-fold approach: (i) the storage of images of past counterfeited documents seized by questioned documents forensic experts of the Portuguese Scientific Laboratory in a structured database; and (ii) the automation of the counterfeit identification by comparing a given fraudulent document image with the database images of previously catalogued counterfeited documents. In general, the proposed information system aims to smooth the counterfeit identification and to overcome the error prone, manual and time consuming tasks carried on by forensic experts. Hence, we have used a scalable algorithm under the OpenCV framework, to compare images, match patterns and analyse textures and colours. The algorithm was tested on a subset of counterfeited Portuguese citizen cards, presenting very promising results.eng
dc.identifier.citationRafael Vieira, Catarina Silva, Mário Antunes, Ana Assis, Information System for Automation of Counterfeited Documents Images Correlation, Procedia Computer Science, Volume 100, 2016, Pages 421-428, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2016.09.178
dc.identifier.doi10.1016/j.procs.2016.09.178
dc.identifier.issn1877-0509
dc.identifier.urihttp://hdl.handle.net/10400.8/13276
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier BV
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S1877050916323468
dc.relation.ispartofProcedia Computer Science
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectInformation systems
dc.subjectFraud detection
dc.subjectPattern Matching
dc.subjectImage Processing
dc.titleInformation System for Automation of Counterfeited Documents Images Correlationeng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage428
oaire.citation.startPage421
oaire.citation.titleProcedia Computer Science
oaire.citation.volume100
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameSilva
person.familyNameAntunes
person.givenNameCatarina
person.givenNameMário
person.identifierR-000-NX4
person.identifier.ciencia-idAF10-7EDD-5153
person.identifier.orcid0000-0002-5656-0061
person.identifier.orcid0000-0003-3448-6726
person.identifier.scopus-author-id25930820200
relation.isAuthorOfPublicationee28e079-5ca7-4842-9094-372c40f75c38
relation.isAuthorOfPublicatione3e87fb0-d1d6-44c3-985d-920a5560f8c1
relation.isAuthorOfPublication.latestForDiscoveryee28e079-5ca7-4842-9094-372c40f75c38

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