计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 57-62.doi: 10.11896/jsjkx.200900218
周俊1,2, 王帅3, 刘凡漪4
ZHOU Jun1,2, WANG Shuai3, LIU Fan-yi4
摘要： 虹膜特征提取是虹膜识别中的关键环节。小波方法在提取虹膜特征时未对分解后的高频空间进一步细化分解,而虹膜纹理特征较多地蕴含在高频空间中,因此提取的虹膜特征在表示特征能力上存在不足。针对此类问题,提出一种基于小波包多尺度分解的虹膜识别方法,利用阈值将小波包分解后第二层对角高频子带图调制为虹膜特征码,利用海明距离对特征进行识别。对108类人眼虹膜图像进行特征提取与匹配,分解小波采用sym2小波,共进行5 350次特征匹配,正确识别率达到98.5%,在识别性能上优于Boles的小波变换过零点法和Lim的二维Haar小波变换法,仅次于Daugman的二维Gabor方法。
中图分类号:
| [1] TIAN Q C,ZHANG R S.Overview of biometric recog-nition technology [J].Computer Application Research,2010,26(12):4401-4410. [2] DAUGMAN J.High confidence visual recognition of persons by a test of statistical independence[J],IEEE Transactions on Pattern Analysis Machine Intelligence,1993,15(11):1148-1161. [3] WILDES R,ASMUTH J C.A system for automated iris recognition[C]//Proceedings of the 2nd IEEE Workshop on Applicant Computer Vision.Sarasota,FL USA,1994:121-128. [4] HE F,HAN Y,WANG H,et al.Deep learning architecture for iris recognition based on optimal Gabor filters and belief network[J].Journal of Electronic Imaging,2017,26(2):023005. [5] YANG X,ZHU X D,LIU Y N,et al.Iris recognition methodbased on block wavelet feature combined with BP neural network [J].Computer Engineering and Applications,2019,55(18):132-139. [6] ZHENG Y P,LI G Y,LI Y.A review of research on the application of deep learning in image recognition[J].Computer Engineering and Applications,2019,55(12):20-36. [7] LIMS S,LEE K,BYEON O,et al.Efficient iris recognitionthrough improvement of feature vector and classifier[J].ETRI Journal,2001,23(2):61-70. [8] BOLES W W,BOASHASH B.A human identification techni-que using images of the iris and wavelet transform[J].IEEE Transactions on Signal Processing,1998,46(4):1185-1188. [9] BAIY C.Research on iris recognition method of visible lightmobile terminal [D].Shenyang:Shenyang University of Technology,2019. [10] KANG B J,PARK K R.A robust eyelash detection based on iris focus assessment [J].Pattern Recognition,2007,28(13):1630-1639. [11] DAUGMAN J.Statistical richness of visual phase information:Update on recognizing persons by iris patterns[J].International Journal of Computer Vision,2001,45(1):25-38. [12] MA L,TAN T,WANG Y,et al.Personal Recognition Based on Iris Texture Analysis[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2003,25(12):1519-1533. [13] MASEK L.Recognition of human iris patterns for biometricidentification[R].Technical Report,School of Computer Science and Software Engineering,University of Western Australia,2003. [14] YANG J G.Wavelet analysis and its engineering application[M].Beijing:Mechanical Industry Press,2009. [15] SUNG H,LIM J,PARK J.Iris Recognition Using CollaretteBoundary Localization[C]//Proceedings of the 17th International Conference on Pattern Recognition.Washington,DC,USA 2004:857-860. [16] FU H Z,XU Y W,LIN S,et al.Angle-Closure Detection in Anterior Segment OCT Based on Multilevel DeepNetwork[J].IEEE Transactions on Cybernetics,2020,50(7). [17] LIU S,LIU Y N,ZHU X D,et al.Iris double recognition based on modified evolutionary neural network[J].Journal of Electronic Imaging,2017,26(6):063023. [18] TIAN Q C.Principle and Algorithm of Iris Recognition [M].Beijing:National Defense Industry Press,2010. [19] JIANG H,MENG D T.Iris recognition based on CS-LBPand adaptive neural network[J].Journal of Northeast Normal University (Natural Science Edition),2018,50(3):58-64. [20] Institute of Automation,Chinese Academy of Sciences.CASIA iris image database [EB/OL].(2007-12-23).http://www.cbsr.ia.ac.cn/English/Irisdatabase.asp. |
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