Enhance the Performance of Directional Feature-based Palmprint Recognition by Directional Response Stability Measurement
文献类型：期刊论文
| 作者 | Haitao Wang ; Wei Jia
|
| 刊名 | Machine Intelligence Research
 |
| 出版日期 | 2024 |
| 卷号 | 21期号:3页码:597-614 |
| 关键词 | Biometrics, palmprint recognition, directional response stability, directional coding-based methods, directional feature |
| ISSN号 | 2731-538X |
| DOI | 10.1007/s11633-023-1436-6 |
| 英文摘要 | Palmprint recognition is an emerging biometrics technology that has attracted increasing attention in recent years. Many palmprint recognition methods have been proposed, including traditional methods and deep learning-based methods. Among the traditional methods, the methods based on directional features are mainstream because they have high recognition rates and are robust to illumination changes and small noises. However, to date, in these methods, the stability of the palmprint directional response has not been deeply studied. In this paper, we analyse the problem of directional response instability in palmprint recognition methods based on directional feature. We then propose a novel palmprint directional response stability measurement (DRSM) to judge the stability of the directional feature of each pixel. After filtering the palmprint image with the filter bank, we design DRSM according to the relationship between the maximum response value and other response values for each pixel. Using DRSM, we can judge those pixels with unstable directional response and use a specially designed encoding mode related to a specific method. We insert the DRSM mechanism into seven classical methods based on directional feature, and conduct many experiments on six public palmprint databases. The experimental results show that the DRSM mechanism can effectively improve the performance of these methods. In the field of palmprint recognition, this work is the first in-depth study on the stability of the palmprint directional response, so this paper has strong reference value for research on palmprint recognition methods based on directional features. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/56485]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China |
| 推荐引用方式 GB/T 7714 | Haitao Wang,Wei Jia. Enhance the Performance of Directional Feature-based Palmprint Recognition by Directional Response Stability Measurement[J]. Machine Intelligence Research,2024,21(3):597-614. |
| APA | Haitao Wang,&Wei Jia.(2024).Enhance the Performance of Directional Feature-based Palmprint Recognition by Directional Response Stability Measurement.Machine Intelligence Research,21(3),597-614. |
| MLA | Haitao Wang,et al."Enhance the Performance of Directional Feature-based Palmprint Recognition by Directional Response Stability Measurement".Machine Intelligence Research 21.3(2024):597-614. |
入库方式： OAI收割
来源：自动化研究所
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