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A Novel and Efficient Method for Iris Automatic Location 被引量:2

A Novel and Efficient Method for Iris Automatic Location
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摘要 An efficient and robust iris location algorithm plays a very important role in a real iris recognition system. A novel and efficient iris automatic location method is presented in this study. It includes following two steps mainly: pu- pil location and iris outer boundary location. A digital eye image was divided into many small rectangular blocks with fixed size in the pupil location, and the block with the smallest average intensity was selected as a reference area. Then image binarization was implemented taking the average intensity of the reference area as a threshold. At last the center coordinates and radius of pupil were estimated by extending the reference area to the pupil's boundaries in the binary iris image. In the iris outer location, two local parts of the eye image were selected and transformed into polar coordinates from Cartesian reference. In order to detect the fainter outer boundary of the iris quickly, a novel edge detector was used to locate boundaries of the two parts. The center coordinates and radius of the iris outer boundary can be estimated using the fusion of the locating results of the two local parts and the location information of the pupil. The algorithm was tested on CASIA vl.0 and MMU vl.0 digital eye image databases and experimental results show that the proposed method has satisfying performance and good robustness. An efficient and robust iris location algorithm plays a very important role in a real iris recognition system. A novel and efficient iris automatic location method is presented in this study. It includes following two steps mainly: pu-pil location and iris outer boundary location. A digital eye image was divided into many small rectangular blocks with fixed size in the pupil location,and the block with the smallest average intensity was selected as a reference area. Then image binarization was implemented taking the average intensity of the reference area as a threshold. At last the center coordinates and radius of pupil were estimated by extending the reference area to the pupil's boundaries in the binary iris image. In the iris outer location,two local parts of the eye image were selected and transformed into polar coordi-nates from Cartesian reference. In order to detect the fainter outer boundary of the iris quickly,a novel edge detector was used to locate boundaries of the two parts. The center coordinates and radius of the iris outer boundary can be esti-mated using the fusion of the locating results of the two local parts and the location information of the pupil. The algo-rithm was tested on CASIA v1.0 and MMU v1.0 digital eye image databases and experimental results show that the proposed method has satisfying performance and good robustness.
出处 《Journal of China University of Mining and Technology》 EI 2007年第3期441-446,共6页 中国矿业大学学报(英文版)
基金 Projects 6057201 supported by the National Natural Science Foundation of China LZ985-231-582627 by the 985 Special Study Project of Lanzhou University
关键词 BIOMETRICS iris recognition iris location pattern recognition 生物测定学 虹膜识别技术 虹膜定位 识别模式
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参考文献11

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同被引文献11

  • 1田启川,潘泉,张洪才,程咏梅.Hough变换在虹膜区域分割中的应用[J].计算机应用研究,2005,22(1):249-250. 被引量:11
  • 2Institute of Chinese Academy of Sciences.CASIA iris image database: (Version 3.0) [EB/OL]. (2006) [2007 -12 -21].http://www.cbsr.ia.ac.cn/IrisDatabase/irislogin.html.
  • 3Cui J.A fast and robust iris location method based on texture segmentation[C]//Proc SPIE,Biometrie Technology for Human Identification, 2004: 401-408.
  • 4Daugman J.New method in iris recognition[J].IEEE Transactions on Systems, Man, and Cybernetics, 2007,37 (5) : 1167-1175.
  • 5Daugman J.How iris recognition works[J].IEEE Transactions on Circuits and Systems for Video Technology,2004, 14( 1 ) :21-30.
  • 6Wildes R P.Iris recognition:An emerging biometfic technology[C]// Proceeding of the IEEE, 1997,85 (9) : 1348-1363.
  • 7Kong W K.Detecting eyelash and reflection for accurate iris segmentation[J].Internet J Pattern Recognition Artif Intell,2003,17(6) : 1025-1034.
  • 8Kong W K,Zhang D.Accurate iris segmentation based on novel reflection and eyelash detection model[C]//Proc Intemet Symposium on Intelligent Multimedia,Video and Speech Processing,2001:263-266.
  • 9康牧,许庆功.基于Prewitt理论的自适应边缘检测算法[J].计算机应用研究,2009,26(6):2383-2386. 被引量:17
  • 10张明慧,张明超,张尧禹.生物识别技术方法研究[J].电脑编程技巧与维护,2011(10):106-106. 被引量:8

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