基于手指静脉网络特征的认证技术研究
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摘要
随着当前社会的信息化、数字化、网络化的飞速发展,生物认证技术成为保障信息安全的一种重要手段。手指静脉网络与其它生物特征认证方式相比,具有不易受日常损伤、成像不易形变、受外界环境影响小和不易伪造等特点,日益成为一种备受关注的生物认证方式。
本文针对手指静脉网络特征的采集与认证的关键技术进行了深入研究。主要的工作包括:
1.设计并实现了一种基于红外光采集器的手指静脉图像采集装置的初级原型系统,为以后实现实用化的采集设备提供了初步的基础。
2.提出了基于局部熵的反锐化掩膜红外手指静脉图像增强算法。有效改善了手指静脉图像中存在的血管清晰度不高,图像灰度分布不均匀的问题。
3.首次提出将基于曲率的屋脊边缘提取算法用于手指静脉网络的构造,直接得到单像素的手指静脉网络骨架。与传统的先分离静脉图像再提取静脉网络骨架的算法相比,该算法简单,而且提高了静脉骨架提取的精度。在静脉骨架基础上采用最小二乘直线拟合法对手指静脉网络进行二次特征提取,得到静脉网络线特征。并通过构造稀疏矩阵得到了稳定的维数统一的特征向量。
4.最后论文尝试了采用四元数模型进行多特征的融合,四元数模型由线段斜率,截距,中点横坐标,中点纵坐标四组特征向量构成。此特征融合算法简单,而目识别率高。
With the rapid development of society informationize, digital and networking, biometric technology is considered as an important technology for information security. Compare with other biometric authentications, the finger vein recognition technology has many advantages. Firstly the finger vein is not easy to be daily damaged. Secondly it is hard to deform. And it is a living body recognition with interior characteristic. Therefore it is become a major concern.
In this paper, the finger vein image collection and authentication are conduct for in-depth study. The main work includes:
1. We have designed and implemented a primal finger vein image acquisition device which based on infrared light. It build a preliminary base for latter to make a ripe device.
2. Proposes a promising finger vein image enhancement algorithm. Under the constraint that keeps original characteristic of finger vein, the method improves contrast of images. The uneven distribution of image grey of the image can be also resolved.
3. Proposes the method based on surface curvature for roof edge detection to extract the vena framework. It can obtain one pixel framework from finger vein image directly. In traditional process the one pixel framework should be acquired after the vena segmented from original image. In contrast with the traditional process the proposed method is more simply and has high precision. After the vena framework has been obtained, the least-squares approximation beeline method is proposed to get the line feature. By constructing a sparse matrix we can get stable dimension of feature vector.
4. Finally, this paper fuse four features by quaternion modulus, this algorithm is straightforward, and get high recognition rate.
本文针对手指静脉网络特征的采集与认证的关键技术进行了深入研究。主要的工作包括:
1.设计并实现了一种基于红外光采集器的手指静脉图像采集装置的初级原型系统,为以后实现实用化的采集设备提供了初步的基础。
2.提出了基于局部熵的反锐化掩膜红外手指静脉图像增强算法。有效改善了手指静脉图像中存在的血管清晰度不高,图像灰度分布不均匀的问题。
3.首次提出将基于曲率的屋脊边缘提取算法用于手指静脉网络的构造,直接得到单像素的手指静脉网络骨架。与传统的先分离静脉图像再提取静脉网络骨架的算法相比,该算法简单,而且提高了静脉骨架提取的精度。在静脉骨架基础上采用最小二乘直线拟合法对手指静脉网络进行二次特征提取,得到静脉网络线特征。并通过构造稀疏矩阵得到了稳定的维数统一的特征向量。
4.最后论文尝试了采用四元数模型进行多特征的融合,四元数模型由线段斜率,截距,中点横坐标,中点纵坐标四组特征向量构成。此特征融合算法简单,而目识别率高。
With the rapid development of society informationize, digital and networking, biometric technology is considered as an important technology for information security. Compare with other biometric authentications, the finger vein recognition technology has many advantages. Firstly the finger vein is not easy to be daily damaged. Secondly it is hard to deform. And it is a living body recognition with interior characteristic. Therefore it is become a major concern.
In this paper, the finger vein image collection and authentication are conduct for in-depth study. The main work includes:
1. We have designed and implemented a primal finger vein image acquisition device which based on infrared light. It build a preliminary base for latter to make a ripe device.
2. Proposes a promising finger vein image enhancement algorithm. Under the constraint that keeps original characteristic of finger vein, the method improves contrast of images. The uneven distribution of image grey of the image can be also resolved.
3. Proposes the method based on surface curvature for roof edge detection to extract the vena framework. It can obtain one pixel framework from finger vein image directly. In traditional process the one pixel framework should be acquired after the vena segmented from original image. In contrast with the traditional process the proposed method is more simply and has high precision. After the vena framework has been obtained, the least-squares approximation beeline method is proposed to get the line feature. By constructing a sparse matrix we can get stable dimension of feature vector.
4. Finally, this paper fuse four features by quaternion modulus, this algorithm is straightforward, and get high recognition rate.
引文
[1]王阳生,中国生物特征识别发展重大进展[J],中国安防产品信息.2005,(02):3'36.
[2]袁智,手指静脉识别技术研究,吉林大学硕士论文,2007年
[3]Finger Vein Authentication:White Paper.Hitachi Ltd.
[4]http://www.slashgear.com/sony-mofria-finger-vein-biometric-system-announced-0232716/
[5]Mulyono,D,Homg Shi Jinn,"A study of finger vein biometric for personal identification",Biometrics and Security Technologies,2008.ISBAST 2008.Intemational Symposium on 23-24April 2008 Page(s):1-8
[6]Lingyu Wang and Graham Leedham."A Thermal Hand Vein Pattern Verification System".Lecture Notes in Computer Science,ICAPR 2005,2005:58-65P
[7]International Biometric Group-Biometrics Market and Industry Report
[8]田捷,杨鑫.生物特征识别技术理论与应用.北京:电子工业出版社,2005
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[12]丁宇航,手背静脉识别技术研究,哈尔滨工业大学博士论文,2006年
[13]Junichi Hashimoto,Finger Vein Authentication Technology and its Future,VLSI Circuits,2006.Digest of Technical Papers.2006 Symposium on 0-0 0 Page(s):5-8
[14]Chengbo Yu,Huafeng Qin,Research on extracting human finger vein pattern characteristics Intelligent Control and Automation,2008.WCICA 2008.7th World Congress on 25-27 June 2008 Page(s):3789-3793
[15]Yu Chengbo,Qing Huafeng;Zhang Lian,A Research on Extracting Low Quality Human Finger Vein Pattern Characteristics,Bioinformatics and Biomedical Engineering,2008.ICBBE 2008.The 2nd Intemational Conference on 16-18 May 2008 Page(s):1876-1879 Digital Object Identifier 10.1109/ICBBE.2008.798
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[2]袁智,手指静脉识别技术研究,吉林大学硕士论文,2007年
[3]Finger Vein Authentication:White Paper.Hitachi Ltd.
[4]http://www.slashgear.com/sony-mofria-finger-vein-biometric-system-announced-0232716/
[5]Mulyono,D,Homg Shi Jinn,"A study of finger vein biometric for personal identification",Biometrics and Security Technologies,2008.ISBAST 2008.Intemational Symposium on 23-24April 2008 Page(s):1-8
[6]Lingyu Wang and Graham Leedham."A Thermal Hand Vein Pattern Verification System".Lecture Notes in Computer Science,ICAPR 2005,2005:58-65P
[7]International Biometric Group-Biometrics Market and Industry Report
[8]田捷,杨鑫.生物特征识别技术理论与应用.北京:电子工业出版社,2005
[9]http://www.022net.com/2006/10-27/424838373174946.html
[10]李铁钢,静脉识别算法研究,吉林大学博士论文,2007年
[11]韩笑,人体手背静脉识别算法研究,吉林大学博士论文,2007年
[12]丁宇航,手背静脉识别技术研究,哈尔滨工业大学博士论文,2006年
[13]Junichi Hashimoto,Finger Vein Authentication Technology and its Future,VLSI Circuits,2006.Digest of Technical Papers.2006 Symposium on 0-0 0 Page(s):5-8
[14]Chengbo Yu,Huafeng Qin,Research on extracting human finger vein pattern characteristics Intelligent Control and Automation,2008.WCICA 2008.7th World Congress on 25-27 June 2008 Page(s):3789-3793
[15]Yu Chengbo,Qing Huafeng;Zhang Lian,A Research on Extracting Low Quality Human Finger Vein Pattern Characteristics,Bioinformatics and Biomedical Engineering,2008.ICBBE 2008.The 2nd Intemational Conference on 16-18 May 2008 Page(s):1876-1879 Digital Object Identifier 10.1109/ICBBE.2008.798
[16]Dai,Yanggang,Huang,Beining,Li,Wenxin;Xu,Zhuoqun,A Method for Capturing the Finger-Vein Image Using Nonuniform Intensity Infrared Light,Image and Signal Processing,2008.CISP '08.Congress on Volume 4,27-30 May 2008 Page(s):501-505 Digital Object Identifier 10.1109/CISP.2008.654
[17]Maio,D.Maltoni,D.Cappelli,R.Wayman,J.L.Jain,A.K.FVC2000:fingerprint verification competition,Pattern Analysis and Machine Intelligence,IEEE Transactions on Publication Date:Mar 2002 Volume:24,Issue:3 On page(s):402-412
[18]Kohir,V.V.;Desai,U.B.;Face recognition.Circuits and Systems,2000.Proceedings.ISCAS 2000 Geneva.The 2000 IEEE International Symposium on Volume 5,28-31 May 2000Page(s):305-308 vol.5
[19]YU Cheng-bo,ZHANG Rui,QIN Hua-fen,Development of An Identity Recognition System Based on CCD Finger Vein Image,SEMICONDUCTOR OPTOELECTRONICS Vol.29 No.3
[20]Lovhoiden G,Deshmukh H,Zanan H D,Clinical evaluation of vein contrast enhancement[J].Proc.SPIE,2002,4 615:61-70.
[21]Zanan H D,Lovhoiden G,Deshmukh H.Design of a clinical vein contrast enhancing profector[J].Proc.SPIE,2001,4 254:204-215.
[22]吉紫娟,包佳,祺用于手指静脉识别的光学系统,湖北教育学院学报,2007年2月,第24卷第2期
[23]黄建元,赵新荣,张长顺,丁海龙,陆永刚,基于CMOS成像器件的手指静脉图像采集方法及装置,第31卷第1期,2009年1月
[24]阮秋琦,数字图像处理,电子工业出版社,2001年
[25]Wenzhan Dai,Kangtai Wang,"An Image Edge Detection Algorithm Based on Local Entropy",Proceedings of the 2007 IEEE International Conference on Integration Technology March 20-24,2007,Shenzhen,China
[26]Y.H.Lee,S.Y.Park,"A study of convex/concave edges and edge-enhancing operators based on the Laplacian",IEEE Trans.Circuits Systems 37(7),July 1990,pp.940-946.
[27]S.K.Mitra,H.Li,I.-S.Lin,T.H.Yu,"A new class of nonlinear filters for image enhancement",Acoustics,Speech,and Signal Processing,vol.4,1991,pp:2525-2528.
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