Name
Abstract | ||
|---|---|---|
In this paper, a new feature descriptor is presented and proposed for personal verification based on near infrared images of hand-dorsa veins. This new feature descriptor is a modification of the previously proposed partition local binary patterns (PLBP) by adding feature weighting, combining multi-scale PLBP and fusion with structure information. While addition of feature weighting aims to reduce the influence of insignificant local binary patterns, combination of multi-scale features aims to get more texture information and fusion with structure feature aims to increase binary information. Testing on a large database with more than two thousand hand-dorsa vein images, Multi-scale PLBP (MPLBP) is shown to be more effective than the original PLBP and Weighted PLBP (WPLBP), and offers a better performance in recognition of hand-dorsa vein images with a correct recognition rate reaching approximately 99% using a simple nearest neighbor (NN) classifier. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-25417-3_37 | BIOMETRIC RECOGNITION, CCBR 2015 |
Keywords | Field | DocType |
Biometrics,Hand-dorsa vein images,Local binary patterns | k-nearest neighbors algorithm,Weighting,Pattern recognition,Computer science,Binary information,Local binary patterns,Artificial intelligence,Biometrics,Classifier (linguistics),Partition (number theory),Vein recognition | Conference |
Volume | ISSN | Citations |
9428 | 0302-9743 | 6 |
PageRank | References | Authors |
0.55 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kefeng Li | 1 | 9 | 2.97 |
| Guangyuan Zhang | 2 | 11 | 4.34 |
| Yiding Wang | 3 | 21 | 3.20 |
| Peng Wang | 4 | 9 | 1.62 |
| Cui Ni | 5 | 9 | 1.62 |