Name
Abstract | ||
|---|---|---|
Palmprints have been broadly used for personal authentication because they are highly accurate and incur low cost. Most previous works have focused on two-dimensional (2-D) palmprint recognition in the past decade. Unfortunately, 2-D palmprint recognition systems lose the shape information when capturing palmprint images. Moreover, such 2-D palmprint images can be easily forged or affected by noise. Hence, three-dimensional (3-D) palmprint recognition has been regarded as a promising way to further improve the performance of palmprint recognition systems. We have developed a simple, but efficient method for 3-D palmprint recognition by using local features. We first utilize shape index representation to describe the geometry of local regions in 3-D palmprint data. Then, we extract local binary pattern and Gabor wavelet features from the shape index image. The two types of complementary features are finally fused at a score level for further improvements. The experimental results on the Hong Kong Polytechnic 3-D palmprint database, which contains 8000 samples from 400 palms, illustrate the effectiveness of the proposed method. (C) 2013 SPIE and IS&T |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1117/1.JEI.22.4.043040 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
three-dimensional palmprint recognition,shape index,local representation,feature fusion | Computer vision,Authentication,Shape index,Pattern recognition,Computer science,Gabor wavelet,Local binary patterns,Feature extraction,Artificial intelligence,Wavelet | Journal |
Volume | Issue | ISSN |
22 | 4 | 1017-9909 |
Citations | PageRank | References |
5 | 0.41 | 22 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bing Yang | 1 | 44 | 8.37 |
| Xiaohua Wang | 2 | 5 | 0.41 |
| Jinliang Yao | 3 | 5 | 0.41 |
| Xin Yang | 4 | 200 | 36.16 |
| Wenhua Zhu | 5 | 5 | 0.41 |