Efficient Rectification of Distorted Fingerprints

被引：17
|
作者：
Gu, Shan [1 ,2 ]
Feng, Jianjiang [1 ,2 ,3 ]
Lu, Jiwen [1 ,2 ]
Zhou, Jie [1 ,2 ]
机构：
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Natl Lab Informat Sci & Technol, Beijing 100084, Peoples R China
[3] Tsinghua Univ, Grad Sch Shenzhen, Shenzhen 518055, Peoples R China
来源：
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | 2018年 / 13卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Distortion rectification; support vector regression; pose estimation; Hough forest; PERFORMANCE; ALGORITHM; SYSTEM;
D O I：
10.1109/TIFS.2017.2745685
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Recently, distortion rectification based on a single fingerprint image has been shown to be able to significantly improve the recognition rate of distorted fingerprints. However, the computational complexity of such a method is too high to be useful in practice. In this paper, we propose a novel method for the rectification of distorted fingerprints, whose speed is over 30 times faster than the existing method. This significant speedup is due to a Hough-forest-based two-step fingerprint pose estimation algorithm and a support vector regressor-based fingerprint distortion field estimation algorithm. Experimental results on public domain databases show that our method can achieve as good rectification performance as the existing method but meanwhile is significantly faster.
引用
收藏
页码：156 / 169
页数：14
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