Name
Abstract | ||
|---|---|---|
The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers' recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1504/IJBM.2015.071949 | IJBM |
Keywords | Field | DocType |
biometrics, concatenated classifier, finger vein verification, decision level fusion, fingerprint, minutiae feature | Computer vision,Feature vector,Economics,Authentication,Pattern recognition,Feature extraction,Robustness (computer science),Fingerprint,Artificial intelligence,Biometrics,Classifier (linguistics),Modal | Journal |
Volume | Issue | ISSN |
7 | 3 | 1755-8301 |
Citations | PageRank | References |
1 | 0.36 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Ma | 1 | 7 | 1.17 |
| P. Popoola Oluwatoyin | 2 | 117 | 3.93 |
| Shuli Sun | 3 | 734 | 52.41 |