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Adaptive Fingerprint Image Enhancement With Emphasis on Preprocessing of Data

机译:强调数据预处理的自适应指纹图像增强

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摘要

This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.
机译:本文提出了一些对基于上下文过滤的自适应指纹增强方法的改进。术语“自适应”表示根据输入的指纹图像自动调整方法的参数。五个处理模块组成了自适应指纹增强方法,其中四个模块在我们提出的系统中进行了更新。因此,提出的整个系统是新颖的。四个更新的处理块是:1)预处理; 2)全局分析; 3)局部分析;和4)匹配过滤。在预处理和局部分析块中,使用了非线性动态范围调整方法。在全局分析和匹配的过滤块中,应用了不同形式的顺序统计过滤器。这些处理块产生了改进的和新的自适应指纹图像处理方法。本文评估部分介绍了更新处理块的性能。该算法针对NIST开发的NBIS软件进行了评估,以在FVC数据库上进行指纹识别。

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