免疫克隆生长算法在手指静脉特征提取中的研究
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摘要
现代社会中,计算机及网络技术的高速发展,信息安全显示出前所未有的重要性。人们希望有一种更加方便可靠的办法来进行身份鉴定,生物特征识别技术给这一切带来可能。手指静脉血管藏匿于身体内部,具有速度快、精度高、安全等级高、活体识别、内部特征、非接触式等独特的优势,有效地解决了传统的生物特征识别技术如指纹等所面临的诸多难题。随着静脉识别技术向着产品化的方向发展,对静脉提取算法的要求越来越高。提取算法在兼顾准确性的基础上,还要重点考虑算法的实时性。
本研究的主要工作集中在以下几个方面:分析了现阶段国内外手指静脉特征提取算法,并通过仿真比较了其优缺点;根据手指静脉图片在变换域中的特点,提出了一种脊波特征提取技术;根据手指静脉对近红外的吸收特性,提出了一种背景图像的构造以得到第一次残差图像,通过调节比例系数得到第二次残差图像,以间接的方式获取静脉的特征;针对低质量静脉图片特征提取容易将噪声错判成静脉信息,将较差的静脉信息错判成噪声。提出了一种基于线性加权(LWF)免疫克隆的手指静脉特征提取算法。该算法促进静脉信息的生长和抑制噪声的干扰;吸取了免疫克隆算法的核心思想,简化了免疫克隆应用到了手指静脉特征识别的片上系统上。
In modern society, the high-speed development of computer and network has shown unprecedented importance of information security. People want to have a more convenient and reliable way for identification, Biometric identification technology has brought it all possible. Finger vein, hidden within the body, has unique advantages in high speed, high precision, live identification and internal features. It’s an effective solution to the traditional biometrics such as fingerprints which face many problems. With the vein recognition technology develops in the direction towards products, the demanding of extraction algorithms on the veins become increasing. Extraction algorithm based on the accuracy, also need to consider the balance of real-time detection.
This study focused on the following aspects: Analyzed the current finger vein feature extraction algorithms,Through simulation and compares their advantages and disadvantages;According to features of the human finger vein images, the algorithm of image feature extraction based on the Ridgelet transformation is presented in this paper;In the consideration of the accuracy of the Extraction-Algorithm, the real time ability of the algorithm is also taken into account. According to the absorption feature of our finger towards the near-infrared, Based on the construction of background image, this paper proposed an approach to obtain the first residual error image, get the second residual error image through adjusting the scale factors, and finally indirectly gain the features of the vein;To solve the misjudgment of noise and vein information in features extraction from low quality images, a novel method based on LWF (Linear weighting function) immune-clone algorithm is proposed in this paper. The method can helps to boost the growth of the vein information and suppress the interference of noise.;Absorbed the idea of the immune clonal algorithm simplified the immune clone method and applied to the finger vein recognition on-chip system.
本研究的主要工作集中在以下几个方面:分析了现阶段国内外手指静脉特征提取算法,并通过仿真比较了其优缺点;根据手指静脉图片在变换域中的特点,提出了一种脊波特征提取技术;根据手指静脉对近红外的吸收特性,提出了一种背景图像的构造以得到第一次残差图像,通过调节比例系数得到第二次残差图像,以间接的方式获取静脉的特征;针对低质量静脉图片特征提取容易将噪声错判成静脉信息,将较差的静脉信息错判成噪声。提出了一种基于线性加权(LWF)免疫克隆的手指静脉特征提取算法。该算法促进静脉信息的生长和抑制噪声的干扰;吸取了免疫克隆算法的核心思想,简化了免疫克隆应用到了手指静脉特征识别的片上系统上。
In modern society, the high-speed development of computer and network has shown unprecedented importance of information security. People want to have a more convenient and reliable way for identification, Biometric identification technology has brought it all possible. Finger vein, hidden within the body, has unique advantages in high speed, high precision, live identification and internal features. It’s an effective solution to the traditional biometrics such as fingerprints which face many problems. With the vein recognition technology develops in the direction towards products, the demanding of extraction algorithms on the veins become increasing. Extraction algorithm based on the accuracy, also need to consider the balance of real-time detection.
This study focused on the following aspects: Analyzed the current finger vein feature extraction algorithms,Through simulation and compares their advantages and disadvantages;According to features of the human finger vein images, the algorithm of image feature extraction based on the Ridgelet transformation is presented in this paper;In the consideration of the accuracy of the Extraction-Algorithm, the real time ability of the algorithm is also taken into account. According to the absorption feature of our finger towards the near-infrared, Based on the construction of background image, this paper proposed an approach to obtain the first residual error image, get the second residual error image through adjusting the scale factors, and finally indirectly gain the features of the vein;To solve the misjudgment of noise and vein information in features extraction from low quality images, a novel method based on LWF (Linear weighting function) immune-clone algorithm is proposed in this paper. The method can helps to boost the growth of the vein information and suppress the interference of noise.;Absorbed the idea of the immune clonal algorithm simplified the immune clone method and applied to the finger vein recognition on-chip system.
引文
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[3]谢剑斌刘通.一种基于优化区域的静脉图像分割算法[J].信号处理,2009.vol.25 no.1
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[30]Wang Kejun; Xiong Xinyan,Gray-scale skeletonization of near-infrared vein patterns using the improved watershed algorithm in vein pattern biometrics[J],Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on 25-27 May 2009 Page(s):241 - 245
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[33]Zhong Bo Zhang; Wu, D.Y.; Si Lian Ma; Jie Ma; Multiscale Feature Extraction of Finger-Vein Patterns Based on Wavelet and Local Interconnection Structure Neural Network [J] IEEE Neural Networks and Brain,2005. ICNN&B '05. International Conference on Volume 2, 13-15 Oct. 2005 Page(s):1081 - 1084
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[37]Khan, M.H.-M.; Subramanian,Representation of Hand Dorsal Vein Features Using a Low Dimensional Representation Integrating Cholesky Decomposition[J],mage and Signal Processing, 2009. CISP '09. 2nd International Congress on 17-19 Oct. 2009 Page(s):1 - 6
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[2]余成波,秦华峰,张莲.基于B样条函数的图像分割分水岭算法研究[J].压电与声光,2008.vol.30 no.3.
[3]谢剑斌刘通.一种基于优化区域的静脉图像分割算法[J].信号处理,2009.vol.25 no.1
[4]康文雄邓飞其.基于最大邻域内差的静脉图像增强和图像分割[J].光学学报,2009.vol,29.no.7
[5] KeJun Wang,QingChang Guo,The Study of Hand Vein Image Processing Medthod[J]. Proceedings of the 6 th World Congress on Intelligent Control and Automation, 2006,June 21-23.
[6]N. Miura,A, Nagasaka and T. Miyatake.Feature extraction of finger vein patterns based on repeated line tracking and its application to personal identification[J]. Machine Vision and Applications 2004, Volume 15 .Page(s): 194–203.
[7]Jian-Da Wu; Siou-Huan Ye,Driver identification using finger-vein patterns with Radon transformand neural network[J],Expert Systems with Applications, Volume 36, Issue 3, Part 2, April 2009, Pages 5793-5799.
[8]Lee, E.C, Park, K.R.Restoration method of skin scattering blurred vein image for finger vein recognition[J].Electronics Letters, October 8 2009, Volume 45, Issue 21.Page(s):1074–1076.
[9]Yu Chengbo,Qin Huafeng.A research on extracting human finger vein pattern characteristics. Proceedings of the 7th World Congress on Intelligent Control and Automation.2008,p 3783-3788.
[10]Yu Chengbo,Qing Huafeng.A Research on Extracting Low Quality Human Finger Vein Pattern Characteristics[C].The 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008.Page(s): 1876-1879.
[11]Xiang Yu, Wenming Yang.A Novel Finger Vein Pattern Extraction Approach for Near-Infrared Image[C].2nd International Congress on Image and Signal Processing, 2009. Page(s): 1-5。
[12]Jinfeng Yang, Jinli Yang. Finger-Vein Segmentation Based on Multi-channel Even-symmetric Gabor Filters. International Conference on Intelligent Computing and Intelligent Systems, ICIS 2009, v 4, p 500-503.
[13] Rigau J.Feixas M.Sbert Metal Medical image segmentation based on mutual information maximization. In Proceedings of MICCAI2004,Saint-Malo, France,2004,135-142P
[14]Wenlong Huang ; Licheng Jiao,Artificial immune kernel clustering network for unsupervised image segmentation[J], Progress in Natural Science 18 (2008) 455–461
[15]WenJie Tian; Yu Geng,Maximum Fuzzy Entropy and Immune Clone Selection Algorithm for Image Segmentation,Information Processing[J], 2009. APCIP 2009. Asia-Pacific Conference on Volume 1, 18-19 July 2009 Page(s):38 - 41
[16]Zhi Jun; Liu Jian-yong,Method of extracting image geometric primitives based on immune algorithm[J],Bio-Inspired Computing[, 2009. BIC-TA '09. Fourth International Conference on 16-19 Oct. 2009 Page(s):1 - 5
[17]Fu Duan; Xiaoqin Li,Image Retrieval Model Based on Immune Algorithm[J],Intelligent Information Technology Application, Workshop on 2-3 Dec. 2007 Page(s):141 - 144
[18]Xu Xinying; Zhang Zhijun,Threshold image segmentation based on granular immune algorithm[J],Control andDecision Conference, 2009. CCDC '09. Chinese 17-19 June 2009 Page(s):3512 - 3515
[19]Hua Bo; Fulong Ma,Baojun Han,SAR image segmentation based on immune algorithm,Control and Automation[J], 2005. ICCA '05. International Conference onVolume 2, 29-29 June 2005 Page(s):1279 - 1282 Vol. 2
[20]Li Hua; Wang Cui,Medical Image Registration Based on More Features and Artificial Immune Algorithm[J],Artificial Intelligence, 2009. JCAI '09. International Joint Conference on 25-26 April 2009 Page(s):469 - 472
[21]Qiong Cao; Hong Zheng,Image Feature Selection Method Based on Immune Encoding Mechanism[J],Natural Computation, 2008. ICNC '08. Fourth International Conference on Volume 6, 18-20 Oct. 2008 Page(s):653 - 657
[22]Hong Zheng; Du Jiaying,Research on Vehicle Image Classifier Based on Concentration Regulating of Immune Clonal Selection[J],Natural Computation, 2008. ICNC '08. Fourth International Conference onVolume 6, 18-20 Oct. 2008 Page(s):671 - 675
[23]Youxin Li; Zongyuan Mao,A Kind of Two-Dimensional Entropic Image Segmentation Method Based on Artificial Immune Algorithm[J],Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on Volume 2, 0-0 0 Page(s):10412 - 10415
[24]Xiaojun Bi;Guifang Jin , Image Segmentation Algorithm Based on Quantum Immune Programming[J],Integration Technology, 2007. ICIT '07. IEEE International Conference on 20-24 March 2007 Page(s):403 - 407
[25]McCoy, D.F.; Devarajan, V.;Artificial immune systems and aerial image segmentation[J],Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation'., 1997 IEEE International Conference on Volume 1, 12-15 Oct. 1997 Page(s):867 - 872 vol.1
[26]Fengxu Guan; Kejun Wang; Research of Finger Vein Recognition Based on Fusion of Wavelet Moment and Horizontal and Vertical 2DPCA[J],Image and Signal Processing, 2009. CISP '09. 2nd International Congress on 17-19 Oct. 2009 Page(s):1 - 5
[27]Jiang Hong; Guo Shuxu; Vein Pattern Extraction Based on the Position-Gray-Profile Curve[J],mage and Signal Processing, 2009. CISP '09. 2nd International Congress on 17-19 Oct. 2009 Page(s):1 - 4
[28]Chengbo Yu; Huafeng Qing,K2DPCA Plus 2DPCA: An Efficient Approach for Appearance Based Object Recognition[J],Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on 11-13 June 2009 Page(s):1– 4
[29]Cheng-Bo Yu; Dong-Mei Zhang; Finger-Vein Image Enhancement Based on Muti-Threshold Fuzzy Algorithm[J],Image and Signal Processing, 2009. CISP '09. 2nd International Congress on17-19 Oct. 2009 Page(s):1 - 3
[30]Wang Kejun; Xiong Xinyan,Gray-scale skeletonization of near-infrared vein patterns using the improved watershed algorithm in vein pattern biometrics[J],Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on 25-27 May 2009 Page(s):241 - 245
[31]Zhongbo Zhang; Siliang Ma; Xiao Han; Multiscale Feature Extraction of Finger-Vein Patterns Based on Curvelets and Local Interconnection Structure Neural Network [J] IEEE Pattern Recognition, 2006. Page(s):145– 148
[32]Hashimoto, J; Finger Vein Authentication Technology and Its Future [J].IEEE Digest of Technical Papers 2006 Page(s):5 - 8
[33]Zhong Bo Zhang; Wu, D.Y.; Si Lian Ma; Jie Ma; Multiscale Feature Extraction of Finger-Vein Patterns Based on Wavelet and Local Interconnection Structure Neural Network [J] IEEE Neural Networks and Brain,2005. ICNN&B '05. International Conference on Volume 2, 13-15 Oct. 2005 Page(s):1081 - 1084
[34] N.Miura, et al, Automatic Feature Extraction from Non-Uniform Finger Vein Image and its Application to Personal Identification[J], IAPR MVA 2002 7-4 p. 252-256 (2002)
[35] N.Miura, et al, Extraction of Finger Vein Patterns Using Maximum Curvature Points in Image Profiles[J], IAPR MVA 2005 8-30 p. 347-350 (2005)
[36]Kumar, A; Prathyusha, K.V,Personal Authentication Using Hand Vein Triangulation and Knuckle Shape[J],Image Processing, IEEE Transactions on Volume 18, Issue 9, Sept. 2009 Page(s):2127 - 2136 [28]Yuhang Ding; Dayan Zhuang,A study of hand vein recognition method[J],Mechatronics and Automation, 2009 IEEE International Conference Volume 4, 29 July-1 Aug. 2009 Page(s):2106 - 2110 Vol. 4
[37]Khan, M.H.-M.; Subramanian,Representation of Hand Dorsal Vein Features Using a Low Dimensional Representation Integrating Cholesky Decomposition[J],mage and Signal Processing, 2009. CISP '09. 2nd International Congress on 17-19 Oct. 2009 Page(s):1 - 6
[38]Ju Han, Kai-Kuang Ma. Rotation-invariant and scale-invariant Gabor features for texture image retrieval.Image and Vision Computing, Volume 25, Issue 9, 1 September 2007, Pages 1474-1481
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