Name
Abstract | ||
|---|---|---|
Several citizen service databases such as, police, national citizen identity, passport and vehicle registration, store both biographical and biometric information containing huge number of records. Achieving scalability and high accuracy for a 1:N person identification task on these databases is a huge challenge. In this work, we propose to use complementary information present in the biographical data along with biometric information of a user to improve 1:N person identification task for large systems. We show that a likelihood ratio based method for score level fusion of the biometric and biographical classifiers results in high accuracy identification as compared to using only the biometric classifiers or the biographical classifiers. |
Year | Venue | Keywords |
|---|---|---|
2012 | Pattern Recognition | biographies,biometrics (access control),image classification,image fusion,visual databases,biographical information,biographical-biometric classifier fusion,biometric information,citizen service database,complementary information,likelihood ratio based method,person identification,score level fusion |
Field | DocType | ISSN |
Computer vision,Biometrics access control,Pattern recognition,Image fusion,Computer science,Artificial intelligence,Biometrics,Contextual image classification,Scalability | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 2 | 0.39 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vivek Tyagi | 1 | 88 | 8.35 |
| Hima P. Karanam | 2 | 5 | 4.29 |
| Tanveer A. Faruquie | 3 | 318 | 24.45 |
| L. Venkata Subramaniam | 4 | 571 | 52.59 |
| Nalini K. Ratha | 5 | 1090 | 93.04 |