Fast Pore Comparison for High Resolution Fingerprint Images Based on Multiple Co-Occurrence Descriptors and Local Topology Similarities
Fast Pore Comparison for High Resolution Fingerprint Images Based on Multiple Co-Occurrence Descriptors and Local Topology Similarities
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DOI：
10.1109/tsmc.2019.2957411
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
Yuanrong Xu;Yao Lu;Guangming Lu;Jinxing Li;Dafan Zhang
中科院分区：
文献类型：
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作者：
Yuanrong Xu;Yao Lu;Guangming Lu;Jinxing Li;Dafan Zhang
基于孔隙的指纹识别已经研究了几十年。为了提高系统的识别精度，人们提出了许多算法。然而，精度的提高总是以速度为代价的。本文提出了一种新的方法来比较毛孔的高分辨率指纹图像使用流行的粗到细的策略。提出了一种多空间成对局部共现描述子，改进了孔隙间相似度的计算。它使用其邻居计算每个孔隙的多个局部同现统计。该方法可以更准确地建立孔隙之间的对应关系。然后，通过使用局部拓扑保持匹配算法来实现对应关系的细化。该算法使用旋转不变的局部结构和孔隙对局部拓扑相似性来计算每个对应的成本。它可以更准确、更有效地去除失配。在两个高分辨率指纹图像库上的实验结果表明，与现有算法相比，该算法在准确性和速度上都有较好的表现。
Pore-based fingerprint recognition has been researched for decades. Many algorithms have been proposed to improve the recognition accuracy of the system. However, the accuracies are always improved at the cost of speed. This article proposes a novel method to compare the pores in high-resolution fingerprint images using the popular coarse-to-fine strategy. A multiple spatial pairwise local co-occurrence descriptor is proposed to improve the calculation of the similarities between pores. It calculates multiple local co-occurrence statistics for each pore using its neighbors. The proposed method can establish correspondences between pores more accurately. The refinement of the correspondences is then achieved by using a local topology-preserving matching algorithm. The algorithm uses rotational invariant local structures and pore pair local topology similarities to calculate the cost of each correspondence. It can remove the mismatches more accurately and efficiently. The experimental results on two high-resolution fingerprint image databases show that the proposed algorithm perform well in both accuracy and speed comparing to the existing algorithms.