Pore detection in fingerprints based on image subtraction and anisotropic diffusion filtering

Rodrigues, Emily S.; Borges, Vinícius Ruela Pereira

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Campo DC	Valor	Lengua/Idioma
dc.contributor.author	Rodrigues, Emily S.	-
dc.contributor.author	Borges, Vinícius Ruela Pereira	-
dc.date.accessioned	2024-06-12T14:25:57Z	-
dc.date.available	2024-06-12T14:25:57Z	-
dc.date.issued	2019	-
dc.identifier.citation	RODRIGUES, Emily S.; BORGES, Vinícius R. P. Pore detection in fingerprints based on image subtraction and anisotropic diffusion filtering. In: 2018 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2018, Miyazaki, Japan. Proceedings [...]. [S. l.]: IEEE, 2019. DOI: 10.1109/SMC.2018.00355.	pt_BR
dc.identifier.uri	http://repositorio2.unb.br/jspui/handle/10482/48227	-
dc.language.iso	eng	pt_BR
dc.publisher	IEEE	pt_BR
dc.rights	Acesso Restrito	pt_BR
dc.title	Pore detection in fingerprints based on image subtraction and anisotropic diffusion filtering	pt_BR
dc.type	Trabalho apresentado em evento	pt_BR
dc.subject.keyword	Impressões digitais	pt_BR
dc.subject.keyword	Poros	pt_BR
dc.subject.keyword	Difusão anisotrópica	pt_BR
dc.identifier.doi	10.1109/SMC.2018.00355	pt_BR
dc.relation.publisherversion	https://ieeexplore.ieee.org/document/8616351	pt_BR
dc.description.abstract1	We describe a methodology for extracting and identifying pores in high resolution fingerprint digital images. The key strategy is based on an image subtraction between two fingerprint images with different smoothness levels. The anisotropic diffusion filter is employed to obtain such smoothed fingerprints, in which the pores are preserved in the first fingerprint, while the second one only presents ridges and valleys, but pores are blurred. The subtraction procedure results in a difference image, in which the pores are characterized by the lower magnitudes. After that, we perform a histogram equalization for enhancing pores and a global thresholding to obtain the pores as binary regions. Finally, such binary image is post-processed for removing false pore detections. Experiments were conducted using the PolyU HRF fingerprint image set and the results showed that the proposed methodology outperformed other filtered-based pore extraction methods considering the true and false pore detection rates.	pt_BR
dc.contributor.affiliation	University of Brasilia, Department of Computer Science	pt_BR
dc.contributor.affiliation	University of Brasilia, Department of Computer Science	pt_BR
dc.description.unidade	Instituto de Ciências Exatas (IE)	pt_BR
dc.description.unidade	Departamento de Ciência da Computação (IE CIC)	pt_BR
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