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Fingerprint Matching Using Correlation and Thin-Plate Spline Deformation Model

机译:使用相关性和薄板样条变形模型的指纹匹配

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One of the difficulties for fingerprint matching lies in the non-linear distortion between fingerprint images originating from same finger. In this paper we present a modification of correlation matching method, which uses Thin-Plate Spline (TPS) as a model for non-linear transformations between two fingerprints. The TPS model is constructed first from the results of a traditional minutia matching algorithm, and by using this model one of the fingerprints is deformed to match the other. After the TPS transformation the correlation scores between the local neighborhood areas of corresponding minutiae pairs and the edges that connect neighboring matched minutiae pairs are calculated and used for final matching score. The FVC2002 DB1 database is used to test the proposed approach. Experimental result shows the improvement when combining TPS deformation model with correlation matching method.
机译:指纹匹配的困难之一在于源自同一手指的指纹图像之间的非线性失真。在本文中,我们介绍了相关匹配方法的修改,该方法使用薄板样条(TPS)作为两个指纹之间非线性变换的模型。 TPS模型首先从传统的METUTIA匹配算法的结果构建,并且通过使用该模型,其中一个指纹变形以匹配另一个指纹。在TPS转换之后,在相应的细节对的本地邻域区域之间的相关分数和连接相邻匹配的细节对的边缘进行计算并用于最终匹配分数。 FVC2002 DB1数据库用于测试所提出的方法。实验结果表明了在与相关匹配方法结合TPS变形模型时改进。

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