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改进的基于梯度的指纹方向场计算方法 被引量：3

Improved Gradient Based Method for the Computation of Fingerprint Orientation Field
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摘要 提出了一种改进的基于梯度的指纹方向场计算方法,主要做了2个方面的工作:深刻分析了归一化对指纹方向场计算结果的影响,提出了一种融合归一化前、后结果的方法;针对已有基于梯度的方向场计算方法存在准确性与抗噪声性矛盾、计算出的方向场结果不连续等缺点,提出了一种改进的计算方向场的窗口模版。实验验证了文中算法的有效性。 In this paper,an improved gradient based method for the computation of fingerprint orientation fields is proposed.Improved method mainly contains two works： fully analyzing the effects of normalization on the orientation results and proposing a approach for combining the orientation field results of ＇before normalization＇ and ＇after normalization＇ together;for overcoming the conflict between accuracy and noise-robustness,the discontinuity of the orientation results,proposing a new template for the computation of orientation field.Experiments prove the effectiveness of our method.
作者 梅园 赵英男 焦峰 王金生
机构地区 南京信息工程大学计算机与软件学院 唐山学院文法系
出处 《武汉理工大学学报》 CAS CSCD 北大核心 2010年第16期6-10,共5页 Journal of Wuhan University of Technology
基金 国家自然科学基金(60702076) 南京信息工程大学科研启动基金
关键词 生物识别技术 自动指纹识别系统 方向场 梯度向量场 梯度向量 归一化 biometrics AFIS orientation field gradient filed gradient vector normalization
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献14

  • 1Kass M, Witkin A. Analyzing Orientated Pattern, Computer Vision[ J ]. Graphics Image Process, 1986,37 (3) : 362-397.
  • 2Jain A K, Hong L, Bolle R. On-line Fingerprint Verification[J ]. IEEE Trans Pattern Anal Machine Intell, 1997,19 (4) : 302- 314.
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二级参考文献17

  • 1聂桂军,吴陈.自动指纹识别系统中连续分布方向图的研究[J].中国图象图形学报（A辑）,2005,10(3):315-319. 被引量：16
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共引文献19

同被引文献15

  • 1Kass M, Witkin A. Analyzing orientation patterns [ J ]. Computer Vision, Graphics, and Image Processing, 1987,37(3) : 362-385.
  • 2Bazen A M, Gerez S H. Systematic methods for the computation of the directional fields and singular points of fingerprints [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7) : 905-919.
  • 3Rao A R, Schunck B G. Computing oriented texture fields[ C]// Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. California: IEEE, 1989: 61-68.
  • 4Mei Y, Sun H J, Xia D S. A gradient-based combined method for the computation of fingerprint' s orientation field [ J ]. Image and Vision Computing, 2009, 27 (8) : 1169-1177.
  • 5Wang Y, Hu J K, Phillips D. A fingerprint orientation model based on 2D Fourier Fxpansion ( FOMFE ) and its application to singular-point detection and fingerprint indexing [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(4) : 573-585.
  • 6Karu K, Jain A K. Fingerprint classification [ J]. Pattern Recog- nition,1996, 17(3) : 389-404,.
  • 7Nagaty K A. On learning to estimate the block directional image of a fingerprint using a hierarchical neural network [J]. Neural Networks, 2003,16( 1 ) : 133-144.
  • 8Ram S, Bisehof H, Brichbauer J. Modelling fingerprint ridge ori- entation using Legendre polynomials [ J ]. Pattern Recognition, 2010, 43(1) : 342-357.
  • 9Jirachaweng S, Hou Z, Yau W Y, et al. Residual orientation modeling for fingerprint enhancement and singular point detection [J]. Pattern Reeoguition,2011,44(2) : 431-442.
  • 10Suetin P K. Orthogonal Polynomials in Two Variables[ M]. Am- sterdam: Gordon and Breach, 1999.

引证文献3

二级引证文献2

武汉理工大学学报
2010年 第16期

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