基于方向场的手指静脉图像增强

Jinfeng Yang, Wanyin Wang
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引用次数: 5

摘要

在实际应用中,手指静脉图像的质量往往很差,因此手指静脉图像增强对于手指静脉识别具有重要意义。本文提出了一种基于定向场的可靠静脉区域增强方法。首先,利用手指静脉图像的横截面曲率自适应估计粗静脉宽度变化场;其次,计算了基于CVWVF约束的线模型的线滤波变换(LFT),用于手指静脉图像的主取向场(POF)生成。第三,利用带CVWVF约束的曲线模型实现曲线滤波变换(CFT),对POF进行细化。利用CFT可以可靠地增强手指静脉图像中的静脉区域。最后,实验结果表明,该方法具有较好的手指静脉图像增强效果。
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Finger-Vein Image Enhancement Based on Orientation Field
Finger-vein image enhancement is of great importance for finger-vein recognition since the quality of the finger-vein images always is very poor in practice. In this paper, a new method based on orientation field is proposed for reliable venous region enhancement. First, a coarse vein-width variation field (CVWVF) is adaptively estimated by the curvatures of the cross-sectional profiles in a finger-vein image. Second, a line filter transform (LFT) based on a line model with CVWVF constraint is computed for a primary orientation field (POF) generation in a finger-vein image. Third, to refine POF, a curve model with CVWVF constraint is used for implementing a curve filter transform (CFT). By CFT, the venous regions can be enhanced reliably in a finger-vein image. Finally, experimental results show that the proposed method has a good performance in finger-vein image enhancement.
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