Finger-vein image quality evaluation based on the representation of grayscale and binary image
Finger-vein image quality evaluation based on the representation of grayscale and binary image
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基于灰度和二值图像表示的指静脉图像质量评价
DOI：
10.1007/s11042-016-4317-y
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发表时间：
2017-02
影响因子：
3.6
通讯作者：
he hexiping
中科院分区：
文献类型：
--
作者：
qin huafeng;chen ziran;he hexiping
在本文中，我们提出了一种新颖的手指静脉图像质量评估方法，用于手指静脉验证系统的注册和认证中的质量控制。首先，采用基于 Radon 变换的模型来评估指静脉灰度图像的质量。其次，为了评估手指静脉二值图像的质量，我们进一步提出了三个评估函数来衡量手指静脉图像二值版本的连通性、平滑度和可靠性。最后，将更精细的静脉二值图像的分数与来自手指静脉灰度图像的分数融合以提高性能。实验结果表明，我们的方法可以有效识别低质量的指静脉图像，这也有助于提高指静脉验证系统的性能。我们还表明，不选择最高质量的图像作为注册模板，而是使用中等质量的模板将在提高变异准确性方面获得更好的性能。
In this paper, we propose a novel quality assessment of finger-vein images for quality control in the enrollment and authentication of a finger-vein verification system. First, a Radon transform based model is employed to assess the quality of a finger-vein grayscale image. Second, to assess the quality of a finger-vein binary image, we further proposed three evaluation functions to measure the connectivity, smoothness and reliability of the binary version of the finger-vein image. Finally, the scores from the finer-vein binary images are fused with these from finger-vein grayscale images to improve the performance. Experimental results show that our approach can effectively identify the low quality finger-vein images, which is also helpful in improving the performance of the finger-vein verification system. We also show that instead of choosing the images with the highest quality as the enrollment templates, using the templates with the mid-range quality would achieve better performance with respect to improvement of varication accuracy.
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DOI：
10.1109/tifs.2008.2007245
发表时间：
2008-12
影响因子：
6.8
作者：
Sanghoon Lee;Heeseung Choi;Kyoungtaek Choi;Jaihie Kim
通讯作者：
Sanghoon Lee;Heeseung Choi;Kyoungtaek Choi;Jaihie Kim
DOI：
10.1109/tifs.2008.924606
发表时间：
2008-09-01
影响因子：
6.8
作者：
Belcher, Craig;Du, Yingzi
通讯作者：
Du, Yingzi
基于迭代四叉树分解的超声乳腺肿瘤图像种子点自动选择
影响因子：
3.6
作者：
["Huaiyu Fan
通讯作者：
["Huaiyu Fan
影响因子：
9
作者：
M. Abdel-Mottaleb;M. Mahoor
通讯作者：
M. Abdel-Mottaleb;M. Mahoor
DOI：
10.1109/icpr.1996.547016
发表时间：
1996-08
期刊：
Proceedings of 13th International Conference on Pattern Recognition
影响因子：
--
作者：
Anil K. Jain;Lin Hong;R. Bolle
通讯作者：
Anil K. Jain;Lin Hong;R. Bolle