| Full text | |
| Author(s): |
da Silva Vasconcelos, Raimundo Claudio
;
Pedrini, Helio
;
Tremeau, A
;
Farinella, GM
;
Braz, J
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 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. |
| Abstract | |
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) | |
| FAPESP's process: | 17/12646-3 - Déjà vu: feature-space-time coherence from heterogeneous data for media integrity analytics and interpretation of events |
| Grantee: | Anderson de Rezende Rocha |
| Support Opportunities: | Research Projects - Thematic Grants |