Name
Abstract | ||
|---|---|---|
Biometrics refer to identity verification of individuals based on some physiologic or behavioural characteristics (face, fingerprint, signature...). The typical authentication process of a person consists in extracting a biometric pattern of him/her and matching it with the stored pattern for the authorized user obtaining a similarity value between patterns. If that similarity is bigger than some threshold the authentication is accepted, otherwise is rejected. Thus, the similarity metrics determine the system ability to successfully classify authentications as authorized or unauthorized. In this work, an analysis of similarity metrics performance is presented for a biometric system in which retinal vessel feature points are used as biometric pattern. The results of the system allow to establish a confidence band for the metric threshold where no errors are obtained for training and test sets. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-69812-8_102 | ICIAR |
Keywords | Field | DocType |
system ability,similarity metrics,similarity metrics performance,metric threshold,authorized user,feature point,similarity metrics analysis,behavioural characteristic,biometric system,retinal authentication,similarity value,biometric pattern,typical authentication process,confidence band | Data mining,Feature point matching,Authentication,Similarity measure,Computer science,Artificial intelligence,Computer vision,Pattern recognition,Retinal vessel feature,Fingerprint,Biometrics,Confidence and prediction bands,Biometric system | Conference |
Volume | ISSN | Citations |
5112 | 0302-9743 | 2 |
PageRank | References | Authors |
0.43 | 12 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M Ortega | 1 | 235 | 37.13 |
| Manuel G. Penedo | 2 | 284 | 24.93 |
| C Mariño | 3 | 48 | 3.25 |
| María J. Carreira | 4 | 134 | 9.81 |