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首页> 外文会议>2016 International Conference on Biometrics >Textured detailed graph model for dorsal hand vein recognition: A holistic approach
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Textured detailed graph model for dorsal hand vein recognition: A holistic approach

机译：用于背手静脉识别的纹理化详细图形模型：一种整体方法

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摘要

Holistic- and local-based methods are two-pronged in dorsal hand vein recognition, and the latter ones have become dominant recently due to their advanced performance. In this paper, we propose a novel approach to dorsal hand vein recognition using a global graph model which takes both the texture and shape cues into account. We first extend the basic graph model consisting of the minutiae of the vein network and their connecting lines to a detailed one by increasing the number of vertices, describing the profile of the vein shape more accurately. We then append the holistic texture feature of the patch around each vertex, i.e. its PCA coefficients, to make the representation of the graph model more comprehensively. The above two steps significantly improve the discrimination of the graph model, and it reports the rank-one recognition rate of 98.82% on the NCUT dataset. This holistic result is comparable to the ones of most local based methods, demonstrating its effectiveness. Meanwhile, with local texture cues embedded, e.g. LBP, HOG, and Gabor, it further reaches the state of the art accuracy up to 99.22%, showing its good complementarity to local based methods.
机译：整体和局部方法在手背静脉识别中有两个方面，而后者由于其先进的性能最近已成为主流。在本文中，我们提出了一种使用全局图模型进行手背静脉识别的新方法，该模型同时考虑了纹理和形状提示。我们首先通过增加顶点数量，将由静脉网络的细部及其连接线组成的基本图形模型扩展为详细的图形模型，从而更准确地描述静脉形状的轮廓。然后，我们将补丁的整体纹理特征附加到每个顶点周围，即其PCA系数，以使图形模型的表示更加全面。以上两个步骤显着改善了图模型的判别力，在NCUT数据集上的排名识别率为98.82％。整体结果可与大多数本地方法相媲美，证明了其有效性。同时，嵌入了局部纹理提示，例如LBP，HOG和Gabor，它进一步达到了最先进的精度，高达99.22％，显示出与基于局部的方法的良好互补性。

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