基于细节聚类和扭曲的指纹匹配方法

Dongjin Kwon, I. Yun, Duck Hoon Kim, Sang Uk Lee
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引用次数: 29

摘要

解决指纹匹配中的非线性失真问题是一个重要且具有挑战性的课题。本文提出了一种新的指纹匹配方法,通过局部匹配的特征聚类和特征聚类对指纹表面进行扭曲,有效地解决了指纹的非线性失真问题。具体来说,利用编码各特征点邻域信息的局部不变结构对匹配的特征点进行聚类,然后对指纹表面进行扭曲,以恰当地描述变形模式。最后,为了进一步提高性能,在分数计算阶段考虑了两枚指纹的重叠区域。实验结果表明,与其他算法相比,该算法具有较好的性能
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fingerprint Matching Method Using Minutiae Clustering and Warping
Solving non-linear distortion problems in fingerprint matching is important and still remains as a challenging topic. We have developed a new fingerprint matching method to deal with non-linear distortion problems efficiently by clustering locally matched minutiae and warping the fingerprint surface using minutiae clusters. Specifically, local invariant structures encoding the neighborhood information of each minutia are utilized in clustering the matched minutiae and then the fingerprint surface is warped to describe the deformation pattern properly. Finally, to make an additional increase in performance, the overlapped region of two fingerprints is considered in the score computation stage. Experimental results show that the proposed algorithm is performed best compared with other ones
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