| Title | A new method for the detection of singular points in fingerprint images |
| Publication Type | Conference Paper |
| Year of Publication | 2009 |
| Authors | Magalhães, F, Oliveira, HP, Campilho, AC |
| Conference Name | 2009 Workshop on Applications of Computer Vision, WACV 2009Workshop Appl. Comput. Vis., WACV |
| Date Published | 2009/// |
| Conference Location | Snowbird, UT |
| ISBN Number | 9781424454976 (ISBN) |
| Keywords | Algorithms, Biometric identifications, Biometrics, Computer applications, Computer vision, Critical steps, Fingerprint analysis, Fingerprint images, Forensic applications, Human intervention, Identification method, Orientation fields, Poincare, Ridge patterns, Singular points, Structural optimization, Technical presentations, Topological structure |
| Abstract | Automatic biometric identification based on fingerprints is still one of the most reliable identification method in criminal and forensic applications. A critical step in fingerprint analysis without human intervention is to automatically and reliably extract singular points from the input fingerprint images. These singular points (cores and deltas) not only represent the characteristics of local ridge patterns but also determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. Poincaré Index-based methods are one of the most common for singular points detection. However, these methods usually result in many spurious detections. Therefore, we propose an enhanced version of the method presented by Zhou et al. [13] that introduced a feature called DORIC to improve the detection. Our principal contribution lies in the adoption of a smoothed orientation field and in the formulation of a new algorithm to analyze the DORIC feature. Experimental results show that the proposed algorithm is accurate and robust, giving better results than the best reported results so far, with improvements in the range of 5% to 7%. © 2009 IEEE. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-77951158127&partnerID=40&md5=718a6649dbc13fcb895f23ffff1363d4 |
