期刊文献+

一种基于相位一致性的虹膜识别方法 被引量:1

Iris Recognition Method Based on Phase Congruency
下载PDF
导出
摘要 由于虹膜具有惟一性、稳定性、不可更改性等优点,虹膜识别已经成为生物特征身份识别领域中的研究热点。为了简化特征提取方法并提高虹膜识别的准确性,提出一种基于相位一致性的虹膜识别方法。该方法利用相位一致性所具有的较强特征检测能力,提取虹膜纹理的边缘点标记纹理的位置信息,将位置特征作为虹膜纹理的可区分性特征实现虹膜识别。在CASIA-IrisV3-Interval图像库上进行实验的结果证明,该方法是可行的,也是有效的,并且具有较高的识别准确性。 Iris recognition has become a research hot-spot in the biometrics recognition filed,because the iris has the properties of unique,stable,unchangeable.an iris recognition method based on phase congruency is proposed,to simplify the method of feature extraction and improre the accuracy of iris recognition,the edge points of iris veins were extracted to mark the location information of iris by utilizing the strong ability for feature detection of phase congruency.It also considers the location feature as the distinguishable feature of iris veins.Experimental results on CASIA-IrisV3-Interval image database demonstrate that the proposed method is feasible and effective,and it has high recognition accuracy.
作者 王恩东
机构地区 沈阳化工学院
出处 《现代电子技术》 2010年第10期93-95,110,共4页 Modern Electronics Technique
关键词 生物特征身份识别 虹膜识别 相位一致性 特征提取 模式匹配 biometrics iris recognition phase congruency feature extraction pattern matching
  • 相关文献

参考文献10

  • 1JAIN A K,ROSS A,PRABHAKAR S.An introduction to biometric recognition[J].IEEE Transactions on Circuits and System for Video Technology,2004,14(1):4-20.
  • 2DAUGMAN J G.Statistical richness of visual phase information:Update on recognizing persons by iris patterns[J].International Journal of Computer Vision,2001.45(1):25-38.
  • 3DAUGMAN J G.How iris recognition works[J].IEEE Transactions on Circuits and Systems for Video Technology,2004,14(1):21-30.
  • 4LIM S,LEE K,BYEON B,et al.Efficient iris recognition through improvement of feature vector and classifier[J].ETRI,2001 23(2):1-70.
  • 5PARK C,LEE J,SMITH M,et al.Iris-based personal authentication using a normalized directional energy feature[J].Proceedings of 4th International Conference on Audioand Video-based Biometric Person Authentication,2003:224-232.
  • 6YUAN Wei-qi,XU Lu,LIN Zhong-hua.An accurate and fast iris location method based on the features of human eyes[C].FSKD 2005,2005,3614:306-315.
  • 7MA Li,TAN Tie-niu,WANG Yunhong,et al.Efficient iris recognition by characterizing key local variations[J].IEEE Transactions on Image Processing,2004,13(6):739-750.
  • 8黄雅平,罗四维,陈恩义.基于独立分量分析的虹膜识别方法[J].计算机研究与发展,2003,40(10):1451-1457. 被引量:16
  • 9Institute of Automation,Chinese Academy of Sciences.CASIA-IrisV3 Database[EB/OL].[2007-04-20].httpt//www.cbsr.ia.ac.cn/IrisDatabase.htm.
  • 10KOVESI P.Phase congruency detects corners and edges[C].Proceedings of the 7th International Conference on Digital Image Computing:Techniques and Applications,Sydney:[s.n.],2003:309-318.

二级参考文献11

  • 1P Kronfeld.Gross anatomy and embryology of the eye.In:The Eye.London:Academic Press,1962.
  • 2H M El-Bakry. Human iris detection using fast cooperative modular neural nets neural networks. Proc of Int'l Joint Conf on IJCNN'01, Washington, 2001.
  • 3John Daugrnan. Neural image processing strategies applied in realtime pattern recognition. Real-Time Imaging, 1997, 3(3): 157-171.
  • 4Shinyoung Lim, Kwanyong Lee, Okhwan Byeon, Taiyun Kim. Efficient iris recognition through improvement of feature vector and classifier. ETRI Journal, 2001, 23(2): 61-70.
  • 5L Flom, A Safir. Iris recognition system. U S Patent, 4641349.1987.
  • 6John Daugrnan. High confidence recognition of persons by iris patterns. The 35th Int'l Carnahan Conf on Security Technology, London, 2001.
  • 7John Daugman. High confidence visual recognition of persons by a test statistical independence. IEEE Trans on Pattern Analysis and Machine Intelligence, 1993, 15(11) : 1148-1161.
  • 8W W Poles, Boashash. A human identification technique using images of the iris and wavelet transform. IEEE Trans on Signal Processing, 1998, 46(4): 1185-1188.
  • 9R P Wildes, J C Asmuth. A system for automated iris recognition. The 2nd IEEE Workshop on Application of Computer Vision, Sarasoto, 1994.
  • 10A HyvLrinen, E Oja. Independent component analysis: Algorithms and application. Neural Networks, 2000, 13(4/5):411 -430.

共引文献15

同被引文献5

引证文献1

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