Department of Electrical Engineering, School of Engineering, Blekinge Institute of Technology, Karlskrona, Sweden.
IEEE Trans Image Process. 2013 Feb;22(2):644-56. doi: 10.1109/TIP.2012.2220373. Epub 2012 Sep 21.
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.
本文提出了对基于上下文滤波的自适应指纹增强方法的几项改进。自适应是指该方法的参数根据输入指纹图像自动调整。自适应指纹增强方法由五个处理块组成，其中四个在我们提出的系统中进行了更新。因此，所提出的整体系统是新颖的。四个更新的处理块是：1）预处理；2）全局分析；3）局部分析；4）匹配滤波。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。在全局分析和匹配滤波块中，应用了不同形式的阶次统计滤波器。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。更新后的处理块的性能在本文的评估部分中给出。该算法是针对 NIST 开发的用于 FVC 数据库上指纹识别的 NBIS 软件进行评估的。
