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An improved finger-vein recognition algorithm based on template matching

机译:一种基于模板匹配的改进的手指静脉识别算法

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Finger-vein recognition has became the most popular biometric identify methods. The investigation on the recognition algorithms always is the key point in this field. So far, there are many applicable algorithms have been developed. However, there are still some problems in practice, such as the variance of the finger position which may lead to the image distortion and shifting; during the identification process, some matching parameters determined according to experience may also reduce the adaptability of algorithm. Focus on above mentioned problems, this paper proposes an improved finger-vein recognition algorithm based on template matching. In order to enhance the robustness of the algorithm for the image distortion, the least squares error method is adopted to correct the oblique finger. During the feature extraction, local adaptive threshold method is adopted. As regard as the matching scores, we optimized the translation preferences as well as matching distance between the input images and register images on the basis of Naoto Miura algorithm. Experimental results indicate that the proposed method can improve the robustness effectively under the finger shifting and rotation conditions.
机译:指静脉识别已成为最流行的生物特征识别方法。对识别算法的研究一直是该领域的关键。到目前为止,已经开发了许多适用的算法。但是,在实践中仍然存在一些问题,例如手指位置的变化可能导致图像失真和移动;在识别过程中,根据经验确定的一些匹配参数也可能降低算法的适应性。针对上述问题,提出了一种基于模板匹配的改进的手指静脉识别算法。为了增强图像失真算法的鲁棒性,采用最小二乘误差法对斜手指进行校正。在特征提取过程中,采用局部自适应阈值法。关于匹配分数,我们基于Naura Miura算法优化了翻译首选项以及输入图像和配准图像之间的匹配距离。实验结果表明,该方法可以在手指移动和旋转的情况下有效地提高鲁棒性。

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