Palm vein recognition based on multi-sampling and feature-level fusion
Palm vein recognition based on multi-sampling and feature-level fusion
复制标题
基于多采样和特征级融合的手掌静脉识别
DOI：
10.1016/j.neucom.2014.10.019
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发表时间：
2015-03
期刊：
影响因子：
6
通讯作者：
Qiuxia Wu
中科院分区：
文献类型：
--
作者：
Xuekui Yan;Wenxiong Kang;Feiqi Deng;Qiuxia Wu
对于非接触式手掌静脉图像，特别是一个图像和下一个图像之间的手定位的实质性变化，由于诸如非均匀照明和仿射变换的问题，难以利用基于几何或几何学的方法实现令人满意的识别性能。为此，本文提出了一种基于多采样和特征级融合的手掌静脉识别方法。由于大多数非接触式手掌静脉图像不清晰，对比度低，如果直接采用SIFT算法对手掌静脉图像的中心区域进行特征提取，将难以获得足够的特征进行有效识别。因此，在本文中，我们首先提出采取整个手掌作为感兴趣区域（ROI），并执行新的层次增强的ROI，以确保额外的功能将获得从后续的特征提取。然后，我们充分利用在注册阶段收集的多个样本，使用特征级融合生成注册模板。最后，提出了双向匹配的失配消除。在CASIA手掌静脉图像数据库和我们采集的手掌静脉数据库上进行的实验表明，该方法在识别性能方面具有上级优势，尤其是对于显著姿态变化下的手掌静脉图像识别。特别是，上述两个数据库的等误差率（EER）值分别为0.16%和0.73%。
For contactless palm vein images, particularly substantial changes in hand positioning between one image and the next, it is difficult to achieve a satisfactory recognition performance with geometry- or statistics-based methods due to issues such as non-uniform illumination and affine transformation. Therefore, with a multi-sampling and feature-level fusion strategy, a novel palm vein recognition method based on local invariant features is presented for addressing the aforementioned issues. As most of the contactless palm vein images are unclear and have low contrast, if a SIFT algorithm is directly adopted for feature extraction on the center region of a palm vein image, it will be difficult to obtain sufficient features for effective recognition. Therefore, in this paper, we first propose to take the entire palm as a Region of Interest (ROI) and perform new hierarchical enhancement on the ROI to ensure that additional features will be obtained from the subsequent feature extraction. Then, we take full advantage of the multiple samples collected in the registration stage to generate the registered template using feature-level fusion. Finally, bidirectional matching is proposed for mismatch removal. The experiments on the CASIA Palm vein Image Database and our palm vein database collected under the posture changes show that the proposed method was superior in terms of recognition performance, especially for palm vein image recognition under remarkable posture changes. In particular, the values of Equal Error Rate (EER) on the aforementioned two databases were 0.16% and 0.73%, respectively.
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DOI：
10.1023/b:visi.0000029664.99615.94
发表时间：
2004-11-01
影响因子：
19.5
作者：
Lowe, DG
通讯作者：
Lowe, DG
DOI：
10.1007/978-0-387-71041-9
发表时间：
2007-10
期刊：
--
影响因子：
--
作者：
Anil K. Jain;P. Flynn;A. Ross
通讯作者：
Anil K. Jain;P. Flynn;A. Ross
DOI：
--
发表时间：
2004
期刊：
--
影响因子：
--
作者：
通讯作者：
--
影响因子：
5.1
作者：
Park, Hyun-Ae;Park, Kang Ryoung
通讯作者：
Park, Kang Ryoung
DOI：
10.1109/cise.2009.5366021
发表时间：
2009-12
期刊：
2009 International Conference on Computational Intelligence and Software Engineering
影响因子：
--
作者：
Xiaohua Qian;Shuxu Guo;Xueyan Li;F. Zhong;Xiangxin Shao
通讯作者：
Xiaohua Qian;Shuxu Guo;Xueyan Li;F. Zhong;Xiangxin Shao