[1]张建明,邱晓晖.基于Curvelet 变换的指纹图像去噪[J].计算机技术与发展,2018,28(05):164-167.[doi:10.3969/j.issn.1673-629X.2018.05.037]
 ZHANG Jianming,QIU Xiaohui.Fingerprint Image Denoising Based on Curvelet Transform[J].,2018,28(05):164-167.[doi:10.3969/j.issn.1673-629X.2018.05.037]
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基于Curvelet 变换的指纹图像去噪()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年05期
页码:
164-167
栏目:
应用开发研究
出版日期:
2018-05-10

文章信息/Info

Title:
Fingerprint Image Denoising Based on Curvelet Transform
文章编号:
1673-629X(2018)05-0164-04
作者:
张建明邱晓晖
南京邮电大学 通信与信息工程学院,江苏 南京 210000
Author(s):
ZHANG Jian-mingQIU Xiao-hui
School of Communication and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210000,China
关键词:
Curvelet 变换阈值函数Wrapping 算法自适应阈值阈值去噪
Keywords:
Curvelet transformthreshold functionWrapping algorithmadaptive thresholdthreshold denoising
分类号:
TN911.73
DOI:
10.3969/j.issn.1673-629X.2018.05.037
文献标志码:
A
摘要:
指纹图像因其具有的终身不变性、唯一性和方便性三大特征在生物特征识别领域发挥着极其重要的作用。然而,指纹在采集和传输的过程中会不可避免地受到外界噪声的污染,从而影响指纹识别系统的准确性。对此,文中采用基于Curvelet 变换的多尺度几何去噪方法,提出对多尺度变换后的各个 Curvelet 子带自适应选取阈值,并结合一种新型阈值函数,克服了传统软硬阈值函数的缺陷。实验结果表明,该方法使得图像中的边缘、直线和曲线特征得到了更好的恢复,而且去噪后的 PSNR 更高,相较于传统阈值处理方法去噪效果更好。
Abstract:
Fingerprint image plays an important role in biometrics because of its lifetime invariance,uniqueness and convenience.However,in the collection and transmission the fingerprint will inevitably be polluted by the noise from outside,thus affecting the accuracy of fingerprint identification system.In this paper,we use the multi-scale geometric denoising method based on Curvelet transform and propose the adaptive threshold selection for each Curvelet sub-band after multi-scale transformation.Then we adopt an improved threshold function to overcome the shortcomings of the traditional soft and hard threshold function.The experiment shows that the proposed method can improve the edge,straight line and curve features in the image,and the PSNR after denoising is higher,with better effect than traditional threshold processing method.

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更新日期/Last Update: 2018-07-06