Name
Abstract | ||
|---|---|---|
A fingerprint recognition algorithm needs to recover the pose transformation between the input fingerprint and the template. One solution is to determine a unique reference point for fingerprint alignment. This work develops a new algorithm to detect a unique reference point consistently for all types of fingerprints. Our detection algorithm works on the orientation field smoothed with an adaptively varying neighborhood. The adaptive window is used to attenuate noise of orientation field effectively while maintaining the detailed orientation information in the high curvature area. A new approach of reference point localization is proposed that is based on hierarchical analysis of the orientation coherence. Experiments demonstrate that our developed algorithm consistently locates a unique reference point with high accuracy for all types of fingerprints. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICPR.2004.751 | ICPR (1) |
Keywords | Field | DocType |
reference point localization,developed algorithm,detection algorithm work,detailed orientation information,unique reference point,fingerprint alignment,orientation coherence,fingerprint recognition algorithm,fingerprint recognition,reference point detection,new algorithm,orientation field,fingerprint identification | Fingerprint alignment,Computer vision,Curvature,Pattern recognition,Computer science,Fingerprint recognition,Fingerprint,Coherence (physics),Image denoising,Artificial intelligence,Hierarchical analysis | Conference |
ISSN | ISBN | Citations |
1051-4651 | 0-7695-2128-2 | 19 |
PageRank | References | Authors |
1.31 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xudong Jiang | 1 | 1885 | 117.85 |
| Manhua Liu | 2 | 323 | 23.91 |
| Alex ChiChung Kot | 3 | 335 | 27.20 |