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A simple approach for biometrics: Finger-knuckle prints recognition based on a Sobel filter and similarity measures

机译:一种简单的生物识别方法:基于Sobel滤波器和相似性度量的指关节指纹识别

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The objective of this work is to propose a novel methodology for the finger knuckle print recognition, which is essentially a digital photo of the finger-knuckle region. We have employed very simple concepts of visual computing such as a filter based on the Sobel operator for finding edges and a simple noise reduction algorithm. These operations are exceptionally fast and produce binary images, which are very efficient to process and to store. Furthermore, alongside this preprocessing, some similarity measures were also regarded and evaluated for the task. After preprocessing an input finger it is compared to all the images of fingers in the dataset, one by one. We have obtained up to 17.02% of successful recognitions (true positive rate) with a large dataset.
机译:这项工作的目的是提出一种用于指节指纹识别的新颖方法,该方法实质上是指节区域的数码照片。我们采用了非常简单的视觉计算概念,例如基于Sobel算子的滤波器来寻找边缘和简单的降噪算法。这些操作异常快速,并且会生成二进制图像,这些二进制图像非常有效地进行处理和存储。此外,除此预处理外,还考虑并评估了该任务的一些相似性度量。在对输入手指进行预处理之后,将其与数据集中手指的所有图像进行逐一比较。我们已经通过大型数据集获得了高达17.02%的成功识别率(真实阳性率)。

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