Name
Abstract | ||
|---|---|---|
This paper presents a new approach to improve the performance of finger-vein identification systems presented in the literature. The proposed system simultaneously acquires the finger-vein and low-resolution fingerprint images and combines these two evidences using a novel score-level combination strategy. We examine the previously proposed finger-vein identification approaches and develop a new approach that illustrates it superiority over prior published efforts. The utility of low-resolution fingerprint images acquired from a webcam is examined to ascertain the matching performance from such images. We develop and investigate two new score-level combinations, i.e., holistic and nonlinear fusion, and comparatively evaluate them with more popular score-level fusion approaches to ascertain their effectiveness in the proposed system. The rigorous experimental results presented on the database of 6264 images from 156 subjects illustrate significant improvement in the performance, i.e., both from the authentication and recognition experiments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TIP.2011.2171697 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
artificial intelligence,feature extraction,imaging,fingerprint identification,image fusion,low resolution,authentication,finger vein recognition,image resolution,biometry,fingerprint recognition,fusion,lighting | Computer vision,Authentication,Image fusion,Pattern recognition,Fingerprint recognition,Fingerprint,Feature extraction,Artificial intelligence,Finger vein recognition,Image resolution,Vein recognition,Mathematics | Journal |
Volume | Issue | ISSN |
21 | 4 | 1941-0042 |
Citations | PageRank | References |
121 | 3.86 | 22 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ajay Kumar | 1 | 1505 | 71.81 |
| Yingbo Zhou | 2 | 263 | 19.43 |