Recovery of Incomplete Fingerprints Based on Ridge Texture and Orientation Field

被引:0
|
作者
Sun, Yuting [1 ]
Chen, Xiaojuan [1 ]
Tang, Yanfeng [1 ]
机构
[1] Changchun Univ Sci & Technol, Sch Elect & Informat Engn, Changchun 130022, Peoples R China
关键词
fingerprint restoration; deep learning; mutilated fingerprints; image processing; IMAGE-ENHANCEMENT; GABOR FILTER;
D O I
10.3390/electronics13142873
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The recovery of mutilated fingerprints plays an important role in improving the accuracy of fingerprint recognition and the speed of identity retrieval, so it is crucial to recover mutilated fingerprints efficiently and accurately. In this paper, we propose a method for the restoration of mutilated fingerprints based on the ridge texture and orientation field. First, the part to be restored is identified via the local quality of the fingerprint, and a mask image is generated. Second, a novel dual-stream fingerprint restoration network named IFSR is designed, which contains two branches, namely an orientation prediction branch guided by the fingerprint orientation field and a detail restoration branch guided by the high-quality fingerprint texture image, through which the damaged region of the mutilated fingerprint is restored. Finally, the method proposed in this paper is validated on a real dataset and an artificially damaged fingerprint dataset. The equal error rate (EER) achieved on the DB1, DB2, and DB4 datasets of FVC2002 is 0.10%, 0.12%, and 0.20%, respectively, while on the DB1, DB2, and DB4 datasets of FVC2004, the EER reaches 1.13%, 2.00%, and 0.27%, respectively. On the artificially corrupted fingerprint dataset, the restoration method achieves a peak signal-to-noise ratio (PSNR) of 16.6735.
引用
收藏
页数:15
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