Name
Title | ||
|---|---|---|
Dual-source discrimination power analysis for multi-instance contactless palmprint recognition |
Abstract | ||
|---|---|---|
Due to the benefits of palmprint recognition and the advantages of biometric fusion systems, it is necessary to study multi-source palmprint fusion systems. Unfortunately, the research on multi-instance palmprint feature fusion is absent until now. In this paper, we extract the features of left and right palmprints with two-dimensional discrete cosine transform (2DDCT) to constitute a dual-source space. Normalization is utilized in dual-source space to avoid the disturbance caused by the coefficients with large absolute values. Thus complicated pre-masking is needless and arbitrary removing of discriminative coefficients is avoided. Since more discriminative coefficients can be preserved and retrieved with discrimination power analysis (DPA) from dual-source space, the accuracy performance is improved. The experiments performed on contactless palmprint database confirm that dual-source DPA, which is designed for multi-instance palmprint feature fusion recognition, outperforms single-source DPA. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11042-015-3058-7 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Biometric fusion systems,Dual-source discrimination power analysis,Multi-instance contactless palmprint recognition,Feature level fusion,Two-dimensional discrete cosine transform | Power analysis,Computer vision,Feature fusion,Normalization (statistics),Pattern recognition,Computer science,Discrete cosine transform,Fusion,Artificial intelligence,Discriminative model,Biometric fusion | Journal |
Volume | Issue | ISSN |
76 | 1 | 1380-7501 |
Citations | PageRank | References |
25 | 0.73 | 39 |
Authors | ||
4 | ||