基于多尺度字典的指纹方向场估计

Chunjie Chen, Jianjiang Feng, Jie Zhou
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引用次数: 10

摘要

方向场估计在指纹识别中具有重要意义。基于字典的算法及其变体——基于局部字典的算法已经显示出良好的性能。在本文中,我们将原来的基于字典的算法扩展到一个多尺度版本。其动机是小规模字典更准确,而大规模字典对图像噪声的鲁棒性更强。因此,可以将不同尺度的方向场信息进行整合,从而获得更好的结果。采用多层磁流变场模型来表述和求解该问题。在具有挑战性的潜在指纹库上的实验结果证明了该算法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-scale dictionaries based fingerprint orientation field estimation
Orientation field estimation is significantly important for fingerprint recognition. Dictionary based algorithm and its variant, localized dictionaries based algorithm have shown promising performance. In this paper, we extend the original dictionary based algorithm to a multi-scale version. The motivation is that small scale dictionary is more accurate while large scale dictionary is more robust against image noise. Hence information from orientation fields of different scales can be integrated to obtain better results. A multi-layer MRF model is used to formulate and solve the proposed problem. Experimental results on challenging latent fingerprint database demonstrate the advantages of the proposed algorithm.
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