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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3JT649H
Repositorysid.inpe.br/sibgrapi/2015/07.22.22.37
Last Update2015:07.22.22.37.19 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2015/07.22.22.37.19
Metadata Last Update2022:05.18.22.21.00 (UTC) administrator
Citation KeySilvaMeno:2015:AbDeLe
TitleUma abordagem para detecção de lentes de contato baseado em Deep Representations
FormatOn-line
Year2015
Access Date2024, May 05
Number of Files1
Size3882 KiB
2. Context
Author1 Silva, Pedro Henrique
2 Menotti, David
EditorVieira, Thales Miranda de Almeida
Mello, Vinicius Moreira
e-Mail Addresspedroh21.silva@gmail.com
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador, BA, Brazil
Date26-29 Aug. 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeUndergraduate Work
History (UTC)2015-07-22 22:37:19 :: pedroh21.silva@gmail.com -> administrator ::
2022-05-18 22:21:00 :: administrator -> :: 2015
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsÍris
Detecção de Lentes de Contato
Aprendizado em Profundidade
Redes Convolucionais
AbstractSpoofing detection is a challenging task in biometric systems, when differentiating illegitimate users from genuine ones. Although iris scans are far more inclusive than fingerprints, and also more precise for person authentication, iris recognition systems are vulnerable to spoofing via textured cosmetic contact lenses. Iris spoofing detection is also referred to as liveness detection (binary classification of fake and real images). In this work, we focus on a three-class detection problem: images with textured (colored) contact lenses, soft contact lenses, and no lenses. Our approach uses a convolutional network to build a deep image representation and an additional fully-connected single layer with softmax regression for classification. Experiments are conducted in comparison with a state-of-the-art approach (SOTA) on two public iris image databases for contact lens detection: 2013 Notre Dame and IIIT-Delhi. The results show that our approach can achieve better results than SOTA on the former database and comparable results on the latter. Despite the proposed approach does not segment iris images, the results for the IIIT-Delhi base reaches values comparable to the SOTA, which segments the images. Taking this into account, we conclude that the results are promising.
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3JT649H
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3JT649H
Languagept
Target File2015-SIBGRAPI-ContactLenses.pdf
User Groupadministrator
pedroh21.silva@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPBW34M/3K24PF8
Citing Item Listsid.inpe.br/sibgrapi/2015/08.03.22.49 10
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsaffiliation archivingpolicy 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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