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Geometric shape analysis based finger vein deformation detection and correction

机译:基于几何形状分析的手指静脉变形检测与矫正

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摘要

Image deformation degrades the performance of finger vein recognition seriously. Some deformation-robust feature extraction and matching methods have been proposed to deal with this problem. However, the deformed image cannot be detected and corrected by these methods. So, it is essential to carry out the image deformation detection and correction in the preprocessing stage. This paper proposes a geometric analysis based detection and correction (GADC) method for deformable finger vein recognition. Specifically, the geometric shape of the finger is analyzed firstly. And then, the deformed finger vein image is detected based on the variation of the finger geometric shape. Lastly, the deformed image is corrected by a linear transformation and a nonlinear transformation. The experiments, on two opened databases and one self-built deformation database, show that our approach can improve the recognition performance of the deformed finger vein images. (C) 2018 Elsevier B.V. All rights reserved.
机译:图像变形严重降低了手指静脉识别的性能。针对这种问题,提出了一些鲁棒的特征提取和匹配方法。但是,这些方法无法检测和校正变形图像。因此,在预处理阶段进行图像变形检测和校正至关重要。本文提出了一种基于几何分析的检测和校正(GADC)方法,用于可变形手指静脉识别。具体地,首先分析手指的几何形状。然后,基于手指几何形状的变化来检测变形的手指静脉图像。最后,通过线性变换和非线性变换来校正变形图像。在两个打开的数据库和一个自建变形数据库上进行的实验表明,我们的方法可以改善手指静脉畸形图像的识别性能。 (C)2018 Elsevier B.V.保留所有权利。

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