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A Local Descriptor with Physiological Characteristic for Finger Vein Recognition

机译:一种具有手指静脉识别的生理特性的本地描述符

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Local feature descriptors exhibit great superiority in finger vein recognition due to their stability and robustness against local changes in images. However, most of these are methods use general-purpose descriptors that do not consider finger vein-specific features. In this work, we propose a finger vein-specific local feature descriptors based physiological characteristic of finger vein patterns, i.e., histogram of oriented physiological Gabor responses (HOPGR), for finger vein recognition. First, a prior of directional characteristic of finger vein patterns is obtained in an unsupervised manner. Then the physiological Gabor filter banks are set up based on the prior information to extract the physiological responses and orientation. Finally, to make the feature robust against local changes in images, a histogram is generated as output by dividing the image into non-overlapping cells and overlapping blocks. Extensive experimental results on several databases clearly demonstrate that the proposed method outperforms most current state-of-the-art finger vein recognition methods.
机译:本地特征描述符由于其稳定性和鲁棒性而对图像的稳定性和稳健性进行了稳定性,因此展示了良好的优势。然而,大多数是方法使用不考虑手指静脉特征的通用描述符。在这项工作中,我们提出了一种基于手指静脉特异性局部特征描述符的手指静脉图案的生理特性,即面向生理葛兰响应(Hopgr)的直方图,用于指静脉识别。首先,以无知的方式获得手指静脉图案的方向特征的前部。然后基于先前信息建立生理Gabor滤波器库,以提取生理反应和方向。最后,为了使特征稳健地抵抗局部图像的局部变化,通过将图像划分为非重叠的小区和重叠块来生成直方图作为输出。在若干数据库上进行了广泛的实验结果,清楚地表明该方法优于最新的最先进的手指静脉识别方法。

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