A New Multi-Filter Framework for Texture Image Representation Improvement Using Set of Pattern Descriptors to Fingerprint Liveness Detection

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Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorFaculty of Architecture and Engineering-
Autor(es): dc.contributorUniversidade Federal de São Carlos (UFSCar)-
Autor(es): dc.creatorContreras, Rodrigo Colnago-
Autor(es): dc.creatorNonato, Luis Gustavo-
Autor(es): dc.creatorBoaventura, Maurilio-
Autor(es): dc.creatorBoaventura, Ines Aparecida Gasparotto-
Autor(es): dc.creatorSantos, Francisco Lledo Dos-
Autor(es): dc.creatorZanin, Rodrigo Bruno-
Autor(es): dc.creatorViana, Monique Simplicio-
Data de aceite: dc.date.accessioned2025-08-21T16:38:52Z-
Data de disponibilização: dc.date.available2025-08-21T16:38:52Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/ACCESS.2022.3218335-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/249355-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/249355-
Descrição: dc.descriptionThe use of user recognition and authentication systems has become very common and is part of everyday routines for many people, guaranteeing access to the automatic teller machines, entrance to the gym or even to smartphones. Among all the biometrics that can be analyzed in this type of system, the fingerprint is the most considered due to the ease of collection, the uniqueness of each user, and the large amount of solid theories and computational libraries available in the scientific literature. However, in recent years, the falsification of these biometrics with synthetic materials, known as spoofing, has become a real threat to these systems. To circumvent these effects without the addition of hardware devices, techniques based on the analysis of texture pattern descriptors were developed. In this work, we propose a new framework based on steps of data augmentation, image processing and replication, and feature fusion and reduction. The method has as main objective to improve the ability of classifiers, or sets of classifiers, to recognize life in fingerprints. Furthermore, it is proposed a generalization of vector representation of patterns described in matrix form from the systematic use of sets of mapping functions. All the proposed material was analyzed on the well-established benchmark of the Liveness Detection competition of the 2009, 2011, 2013 and 2015 editions, presenting an average accuracy of 97.77% and being a competitive strategy in relation to the other techniques that make up the state of the art of specialized literature.-
Descrição: dc.descriptionInstitute of Mathematical and Computer Sciences University of São Paulo, São Carlos-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University São José Do Rio Preto-
Descrição: dc.descriptionMato Grosso State University Faculty of Architecture and Engineering, Cáceres-
Descrição: dc.descriptionFederal University of São Carlos Computing Department, São Carlos-
Descrição: dc.descriptionInstitute of Biosciences Letters and Exact Sciences São Paulo State University São José Do Rio Preto-
Formato: dc.format117681-117706-
Idioma: dc.languageen-
Relação: dc.relationIEEE Access-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectcomputer vision-
Palavras-chave: dc.subjectFingerprint liveness detection-
Palavras-chave: dc.subjectpattern recognition-
Palavras-chave: dc.subjectspoofing detection-
Palavras-chave: dc.subjecttexture analysis-
Título: dc.titleA New Multi-Filter Framework for Texture Image Representation Improvement Using Set of Pattern Descriptors to Fingerprint Liveness Detection-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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