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Research and implementation of finger-vein recognition algorithm

机译:手指静脉识别算法的研究与实现

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In finger vein image preprocessing, finger angle correction and ROI extraction are important parts of the system. In this paper, we propose an angle correction algorithm based on the centroid of the vein image, and extract the ROI region according to the bidirectional gray projection method. Inspired by the fact that features in those vein areas have similar appearance as valleys, a novel method was proposed to extract center and width of palm vein based on multi-directional gradients, which is easy-computing, quick and stable. On this basis, an encoding method was designed to determine the gray value distribution of texture image. This algorithm could effectively overcome the edge of the texture extraction error. Finally, the system was equipped with higher robustness and recognition accuracy by utilizing fuzzy threshold determination and global gray value matching algorithm. Experimental results on pairs of matched palm images show that, the proposed method has a EER with 3.21% extracts features at the speed of 27ms per image. It can be concluded that the proposed algorithm has obvious advantages in grain extraction efficiency, matching accuracy and algorithm efficiency.
机译:在手指静脉图像预处理中,手指角度校正和ROI提取是系统的重要部分。在本文中,我们提出了一种基于静脉图像质心的角度校正算法,并根据双向灰度投影方法提取ROI区域。灵感来自于那些静脉区域的特征具有与谷的外观相似,提出了一种基于多向梯度的棕榈静脉的中心和宽度,这是易于计算,快速稳定的。在此基础上,设计了编码方法来确定纹理图像的灰度值分布。该算法可以有效地克服纹理提取误差的边缘。最后,通过利用模糊阈值确定和全局灰度值匹配算法,该系统具有更高的鲁棒性和识别准确性。对匹配棕榈图像成对的实验结果表明,所提出的方法具有3.21%的速度,以3.21%的提取速度为每图像27ms。可以得出结论,所提出的算法具有明显的晶粒提取效率优势,匹配精度和算法效率。

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