High resolution fingerprint recognition using pore and edge descriptors
High resolution fingerprint recognition using pore and edge descriptors
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DOI：
10.1016/j.patrec.2019.08.006
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发表时间：
2019-07
期刊：
影响因子：
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通讯作者：
Yuanrong Xu;Guangming Lu;Yao Lu;David Zhang
中科院分区：
文献类型：
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作者：
Yuanrong Xu;Guangming Lu;Yao Lu;David Zhang
毛孔用于指纹识别已有很多年了。将毛孔引入指纹图像比对可以提高识别准确率。本文提出了一种比较高分辨率指纹图像上毛孔的新方法。该方法由三个步骤组成。第一步，使用 Root-SIFT 描述符对不同图像上的孔隙进行聚类。然后，将使用旋转不变边缘描述符和霍夫变换来比较同一类中的孔隙。该描述符由三部分组成：边缘的长度、边缘与孔隙方向之间的角度以及孔隙方向之间的角度。在最后一步中，根据匹配的边缘建立孔隙的一对一对应关系，然后利用孔隙的空间关系进行细化。为此，设计了一种基于图的细化算法。在两个高分辨率指纹图像数据库上的实验结果表明，该算法比其他最先进的孔隙比较算法更准确。
Pores have been used for fingerprint recognition for many years. Introducing pores into fingerprint image comparison can improve the recognition accuracy. This paper proposes a novel method to compare pores on high resolution fingerprint images. The method consists of three steps. In the first step, pores on different images are clustered using a Root-SIFT descriptor. Then the pores in the same class will be compared using a rotational invariant edge descriptor and Hough transform. The descriptor consists of three parts: the length of the edge, the angles between the edge and the orientations of pores, and the angle between the orientations of pores. In the final step, one-to-one correspondences of pores are established based on the matched edges, and then refined using the spatial relations of the pores. To this end, a graph based refinement algorithm is designed. Experimental results on two high resolution fingerprint image databases show that the proposed algorithm is more accurate than other state-of-the-art pore comparison algorithms.