期刊文献+

基于线性模板和模糊规则的虹膜坑洞纹理检测 被引量:11

Iris crypt texture detection based on linear template and fuzzy rules
下载PDF
导出
摘要 基于虹膜表面特定形状纹理的虹膜识别方法是虹膜识别的一种有效手段。然而,由于虹膜纹理复杂多样,形态各异,因此如何快速、准确地检测出虹膜表面各种不同类型的特征纹理仍然是目前亟待解决的一个难题。针对坑洞纹理的检测,提出一种基于定长线性模板和模糊规则的虹膜坑洞纹理的检测方法,首先使用一个定长的线性模板提取出虹膜表面所有纹理的边缘。然后,根据坑洞纹理与其他类型的纹理在形状上存在的不同,定义相应的模糊规则,从各种不同类型的纹理中识别出坑洞纹理。该算法对图库中人工标定的坑洞纹理检测的正确率为86.06%;对色素斑、裂缝以及眼睑的排除率分别为84.62%,71.56%,100%。实验结果表明,该方法能够从背景复杂的可见光虹膜图像中识别出坑洞纹理,为虹膜的特征提取提供了一个新的思路。 Iris detection method based on specific shape textures on the iris surface is a kind of effective iris identification method. Due to the facts that iris textures are very complex and have many different kinds of shapes,by now,how to fast and accurately detect all different kinds of feature textures is still a challenging task to be solved. Aiming at the issue of crypt texture detection,an iris crypt texture detection method based on fixed- length linear template and fuzzy rules is proposed in this paper. Firstly,a fixed-length linear template is applied to extract all the edges of all specific shape textures on the iris surface. And then,according to the differences between crypt textures and other kinds of textures in shape,a series of fuzzy rules are defined to detect the crypt textures from all kinds of different types of textures. To test the performance of this method,the method was used to detect the crypts that were artificially marked in our image gallery,and the detection accuracy is 86. 06%; the exclusion accuracies of pigmentary patch,furrow and eyelid are 84. 62%,73. 34% and 100%,respectively. The experiment results show that the proposed method can detect the crypt textures from the visible iris images with complex background and provides a new idea for iris feature extraction.
出处 《仪器仪表学报》 EI CAS CSCD 北大核心 2015年第6期1363-1371,共9页 Chinese Journal of Scientific Instrument
基金 国家自然科学基金(61271365)项目资助
关键词 虹膜坑洞纹理 模糊规则 线性模板 iris crypt texture fuzzy rule linear template
  • 相关文献

参考文献21

  • 1WILDES R P. Iris recognition : An emerging biometrictechnology [J]. Proceedings of the IEEE, 1997,85(9):1348-1363.
  • 2BOLES W W, BOASHASH B. A human identification tech-ni(|ue using images of the iris and wavelet transform [ J ].IEEE Transactions on Signal Processing, 1998,46(4):1185-1188.
  • 3DAUGMAN J. How iris recognition works[J]. IEEE Trans-actions on Circuits and Systems for Video Technology, 2004,14(l):21-30.
  • 4MA L, TAN T,WANG Y,et al. Efficient iris recogni-tion by charac terizing key local variations [ J ]. IEEETransac tions on Image Processing, 2004, 13 ( 6 ):739-750.
  • 5苑玮琦,冯琪,柯丽.基于单频2D-Gabor滤波器的虹膜识别算法研究[J].光学技术,2010,36(1):20-24. 被引量:4
  • 6TSAI C C, LIN H Y,TAUR J, et al. Iris recognitionusing possibilistic fuzzy matching on local features [ J ].IEEE Transaction on systems, Man, and Cybernetics,Part B:Cybernetics, 2012, 42(1) : 150-162.
  • 7苑玮琦,刘博.基于空域与频域稳定特征融合的离焦虹膜识别[J].仪器仪表学报,2013,34(10):2300-2308. 被引量:10
  • 8HOSSEINI M S, ARAABI B N, SOLTANIAN-ZADEH H.Pigment melanin : Pattern for iris recognition [ J ]. IEEETransactions on Instrumentation and Measurement, 2010,59(4);792-804.
  • 9LIANG H, CAI Z, CHEN X, et al. Iris recognitionbased on characters of Iris’ s speckles [ C ]. 7 th WorldCongress on Intelligent Control and Automation,2008 :6793-6797.
  • 10SHEN F,FLYNN P J. Iris matching by crypts and anti-crypts [C ]. 2012 IEEE Conference on Technologies forHomeland Security( HST),2012:208-213.

二级参考文献102

共引文献59

同被引文献91

  • 1辛国栋,王巍.计算机辅助虹膜诊断中特征提取方法研究[J].计算机工程与设计,2006,27(18):3322-3323. 被引量:2
  • 2苑玮琦,林忠华,徐露.一种基于人眼结构特征的新颖虹膜定位算法[J].光电工程,2007,34(1):112-116. 被引量:23
  • 3郎方年,周激流,闫斌,宋恩彬,钟凡.四元数与彩色图像边缘检测[J].计算机科学,2007,34(11):212-216. 被引量:11
  • 4WILDES R P. Iris recognition: An emerging biometric technology[ J]. Proceedings of the IEEE, 1997, 85 (9) : 1348-1363.
  • 5BOLES W W, BOASHASH B. A human identification technique using images of Ihe iris mid wavelet tl'mlsfoml[ J]. IEEE Transactions on Signal 15"ocessing, 1998, 46 ( 4 ) : 1185-1188.
  • 6DAUGMAN J. How iris recognition works [ J ]. IEEE Transactions on Circuits and Systenr'~ for "Video Techno|og, y, 2004,14( I ) :21-30.
  • 7TSAI C C, LIN H Y, TAUR J, et al. Iris recognition u- sing pc~ssihilistic fuzzy matching ~m l~x'al features [ J ]. IEEE Transaction on systems, Man, anti Cybernetics, Part B:Cyhernetics, 2012, 42( 1 ) : 150-162.
  • 8HOSSEINI M S, ARAABI B N, SOIXANIAN-ZADEH H. Pigment melanin: Pattern for iris recognition [ J ]. IEEE Transactions on lnstmmentalion and Measurement, 2010, 59(4) :792-804.
  • 9SHEN F, FLYNN P J. Iris matehing by ct'ypls and anti- crypts[ C~. IEEE Conference on Technologies for Home- land Security (HST), 2012:208-213.
  • 10SUNDER M S, ROSS A. lris image retrieval based on macro-features[ C]. The 20th IEEE International Confer- ence on Pattern Recognition ( ICPR ) , 2010 : 1318-1321.

引证文献11

二级引证文献77

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部