| Texto completo | |
| Autor(es): |
da Silva Vasconcelos, Raimundo Claudio
;
Pedrini, Helio
;
Tremeau, A
;
Farinella, GM
;
Braz, J
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 5; v. N/A, p. 8-pg., 2019-01-01. |
| Resumo | |
Segmentation is a crucial task in automatic fingerprint identification systems. This paper describes a novel segmentation approach which takes into account the directional information inherent in fingerprint ridges. The method considers a directional operator to feed a k-means unsupervised clustering algorithm that labels the image in non-overlapping regions. Morphological operations are performed to fill holes and properly separate foreground from background. Experiments conducted on Fingerprint Verification Competition (FVC) datasets demonstrate that the proposed method, denoted as Oriented Pattern-based Segmentation (OPS), achieves competitive results when compared to other well-known available fingerprint segmentation approaches. (AU) | |
| Processo FAPESP: | 17/12646-3 - Déjà vu: coerência temporal, espacial e de caracterização de dados heterogêneos para análise e interpretação de integridade |
| Beneficiário: | Anderson de Rezende Rocha |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |