Detecção de impressões digitais fraudulentas utilizando padrões mapeados localmente em multiescala

Detalhes bibliográficos
Ano de defesa: 2015
Autor(a) principal: Contreras, Rodrigo Colnago [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/136662
http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/24-03-2016/000859900.pdf
Resumo: Applications which use fingerprint recognition are present in many contexts of everyday life, for example, transactions at ATMs, electronic registration point in companies and, since 2008, in the Brazilian electoral process. The fingerprint matching is usually made based on the relative positions of small patterns known as minutiae. Recent scientific researches show the possibility of making synthetic fingerprints, which have a copy of these minutiae in an authentic finger, from simple materials such as play dough, silicone, wood glue, among others. Faced with the imminent danger of fraud in biometric systems, a new line of research emerged: the detection of fake fingerprints (spoofs). Currently, they are in the literature some methods to minimize this problem, but this is still an open problem. The present study focuses on the detection of fake fingerprints using image processing and pattern recognition techniques. The main contribution of this study is a new technique with which the fakes one are detected from the analysis of spatial micro patterns extracted from the fingerprints. Moreover, it is developed in this work, the multi-scale version of the space micro pattern known as Local Mapped Pattern (LMP). The experiments carried out have shown that through the proposed technique, it is possible to achieve a higher detection performances with the results found state of the art in the specialized literature