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Multi-scale dictionaries based fingerprint orientation field estimation

机译:基于多尺度词典的指纹方向场估计

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摘要

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.
机译:方向场估计对于指纹识别非常重要。基于字典的算法及其变体,基于局部字典的算法已显示出令人鼓舞的性能。在本文中,我们将基于原始字典的算法扩展到多尺度版本。其动机是小规模字典更准确,而大规模字典对图像噪声更健壮。因此,可以整合来自不同尺度的定向场的信息以获得更好的结果。使用多层MRF模型来制定和解决所提出的问题。在具有挑战性的潜在指纹数据库上的实验结果证明了该算法的优势。

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