论文标题
通过多刺融合质地特征的基于棕榈树的个人识别的实验结果
Experimental results on palmvein-based personal recognition by multi-snapshot fusion of textural features
论文作者
论文摘要
在本文中，我们研究了质地特征的多个快照融合，以识别棕榈树的识别，包括识别和验证。尽管文献提出了棕榈藤识别的几种方法，但棕榈素性能仍会受到识别和验证错误的影响。众所周知，通常通过基于线的方法来描述棕榈树，从而增强静脉流量。据称这是一个人到一个人的独特之处。但是，棕榈藤图像还具有纹理的特征，可以用纹理特征指出，这些特征依赖于最近有效的手工制作的算法，例如本地二进制图案，本地相量化，本地TERA模式，本地定向模式，局部定向模式以及二进制统计图像（LBP，LPQ，LPQ，LTP，LDP，LDP和其他）等。最后，当可以获取多个样本以识别时，可以轻松地在功能级融合中对其进行管理。因此，可以采用多SNAPSHOT融合来利用这些功能互补性。我们本文的目标是证明这是棕榈素识别的确认，因此可以在众所周知的基准数据集上实现很高的识别率。
In this paper, we investigate multiple snapshot fusion of textural features for palmvein recognition including identification and verification. Although the literature proposed several approaches for palmvein recognition, the palmvein performance is still affected by identification and verification errors. As well-known, palmveins are usually described by line-based methods which enhance the vein flow. This is claimed to be unique from person to person. However, palmvein images are also characterized by texture that can be pointed out by textural features, which relies on recent and efficient hand-crafted algorithms such as Local Binary Patterns, Local Phase Quantization, Local Tera Pattern, Local directional Pattern, and Binarized Statistical Image Features (LBP, LPQ, LTP, LDP and BSIF, respectively), among others. Finally, they can be easily managed at feature-level fusion, when more than one sample can be acquired for recognition. Therefore, multi-snapshot fusion can be adopted for exploiting these features complementarity. Our goal in this paper is to show that this is confirmed for palmvein recognition, thus allowing to achieve very high recognition rates on a well-known benchmark data set.
