基于手部特征识别关键技术的研究与实现
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摘要
为了解决基于手部特征的识别技术实用化进程中存在的问题,本文对基于多层次、多特征的手部生物特征图像进行分析来实现人身份的鉴别,并对基于图像内容的手部生物特征的识别技术进行了较为深入的研究。本文主要研究了基于手部生物特征的识别技术中包括多指指纹图像获取技术,多指指纹图像有效区域的分割,手部血管图像的采集技术,血管特征提取算法,纹形分类技术等关键问题的研究。
本文首先探讨了手部生物特征的特点,并对基于手部生物特征的识别系统及关键技术进行详细的归纳总结。其次,为了解决海量指纹数据库检索耗时大、复杂性高和不精确的问题,提出基于指纹奇异点结构的纹形分类方法。再次,本文给出了基于光学技术的多指指纹采集方案及实现方法,以及基于光学技术的人体手足末端血管采集的实现；最后研究并提出了多尺度曲率下的血管图像ROI自动检测定位的新算法,实现ROI的精准定位。
Biometrics is the measurement and analysis of biological data, science and technology, is used to measure, statistics and analysis of biological data, a discipline and technology, using human physiological or behavioral characteristics to identify the unique user identity. Read in full on the basis of large number of documents, the paper covered areas of research the status of the analysis and research later, the Ministry for human exposure to hand-based biometric identification technology, with the current trends in research and development, this Department starting from a variety of Hand features biometric collection technology, working on hand a number of key biometric technologies, including image acquisition based on optical technology, technical studies, access to image quality assessment, biological feature extraction and matching technology, combined with information and sensor fusion theory and hands Department of feature recognition applications, to achieve technological innovation. For more content, the organization of this paper consists of five parts:
The first part is the summary of this thesis, and it describes the purpose of this paper and the subject of the source, and then describes the identity-based biometric authentication technology researches and the problems are still in existence. In the finally, an overview of the main contents of this article, by the introduction of biometric identification technology background, significance, research and application at home and abroad to start on the dissertation research and explain the contents of arrangements;
The second part of this paper, which is hand-based biometric identification technology, is the information theory and the test database. Hand biometric image is part of the whole system is based on the sample set to establish inspection and evaluation system has played an important role, helping the follow-up process.
The third part of the optical system based on fingerprint technology and multi-fingered hand of human vascular optical image capture technology. Hand biometric image acquisition is an important part of the whole system, collecting device is a recognition algorithm based on a direct impact on image quality, image acquisition device for quality assessment needed to help the follow-up process. This section is proposed and implemented an optical system of the vascular image acquisition technology, and on this basis builds a biometric database of hand features;
The fourth part of the hand-based biometric authentication system, the key issue. Fingerprint recognition technology in terms of the theory of algorithms or from the engineering point of view, and the research results are rich. Fingerprint feature extraction, feature points up than the other already has a very mature technology, but for large networks based on the system than the recognition speed to be improved, this article from the biometric identification system of hand the key problems start, in Research on the search strategy, given the large search strategy than the system. This section also presented in this chapter the multi-scale curvature analysis method to obtain blood vessel model, focused on the study of vascular pattern extraction algorithm, the angle of curvature analysis of multiple blood vessels extraction issues.
The fifth chapter is experimental and conclusions of each chapter, and the prospects for future work.
本文首先探讨了手部生物特征的特点,并对基于手部生物特征的识别系统及关键技术进行详细的归纳总结。其次,为了解决海量指纹数据库检索耗时大、复杂性高和不精确的问题,提出基于指纹奇异点结构的纹形分类方法。再次,本文给出了基于光学技术的多指指纹采集方案及实现方法,以及基于光学技术的人体手足末端血管采集的实现；最后研究并提出了多尺度曲率下的血管图像ROI自动检测定位的新算法,实现ROI的精准定位。
Biometrics is the measurement and analysis of biological data, science and technology, is used to measure, statistics and analysis of biological data, a discipline and technology, using human physiological or behavioral characteristics to identify the unique user identity. Read in full on the basis of large number of documents, the paper covered areas of research the status of the analysis and research later, the Ministry for human exposure to hand-based biometric identification technology, with the current trends in research and development, this Department starting from a variety of Hand features biometric collection technology, working on hand a number of key biometric technologies, including image acquisition based on optical technology, technical studies, access to image quality assessment, biological feature extraction and matching technology, combined with information and sensor fusion theory and hands Department of feature recognition applications, to achieve technological innovation. For more content, the organization of this paper consists of five parts:
The first part is the summary of this thesis, and it describes the purpose of this paper and the subject of the source, and then describes the identity-based biometric authentication technology researches and the problems are still in existence. In the finally, an overview of the main contents of this article, by the introduction of biometric identification technology background, significance, research and application at home and abroad to start on the dissertation research and explain the contents of arrangements;
The second part of this paper, which is hand-based biometric identification technology, is the information theory and the test database. Hand biometric image is part of the whole system is based on the sample set to establish inspection and evaluation system has played an important role, helping the follow-up process.
The third part of the optical system based on fingerprint technology and multi-fingered hand of human vascular optical image capture technology. Hand biometric image acquisition is an important part of the whole system, collecting device is a recognition algorithm based on a direct impact on image quality, image acquisition device for quality assessment needed to help the follow-up process. This section is proposed and implemented an optical system of the vascular image acquisition technology, and on this basis builds a biometric database of hand features;
The fourth part of the hand-based biometric authentication system, the key issue. Fingerprint recognition technology in terms of the theory of algorithms or from the engineering point of view, and the research results are rich. Fingerprint feature extraction, feature points up than the other already has a very mature technology, but for large networks based on the system than the recognition speed to be improved, this article from the biometric identification system of hand the key problems start, in Research on the search strategy, given the large search strategy than the system. This section also presented in this chapter the multi-scale curvature analysis method to obtain blood vessel model, focused on the study of vascular pattern extraction algorithm, the angle of curvature analysis of multiple blood vessels extraction issues.
The fifth chapter is experimental and conclusions of each chapter, and the prospects for future work.
引文
[1]A. K. Jain, P. Flynn, A. Ross, Handbook of Biometrics [M], Springer, 2007.
[2]V. Roman, Yampolskiy, and Venu Govindaraju, Behavioural biometrics: a survey and classification [J], International Journal of Biometrics, Vol.1, No.1,2008, pp.81-113.
[3]A. K. Jain, Biometric Recognition:Overview and Recent Advances, Lecture Notes in Computer Science[R],2007, Vol.4756, pp.13-19.
[4]Stan Z. Li, Ben Schouten, Massimo Tistarelli, Biometrics at a Distance:Issues, Challenges, and Prospects [M], Springer,2009.
[5]Massimo Tistarelli,3D Face Recognition:Technology and Applications [M], Springer,2009.
[6]Yoshida Kazuhiko, Honma Shota, Ohtsuka Tomohiko, Aoki Hiroyuki, New Fingerprint Minutiae Extraction Using Ridge Flux Analysis [C], Asia Pacific Signal and Information Processing Association,2009.
[7]Jianjiang Feng, Combining minutiae descriptors for fingerprint matching [J], Pattern Recognition, Vol.41,2008, pp.342-352.
[8]Haiyun Xu, Raymond N.J., Spectral Minutiae Representations for Fingerprint Recognition [C],2010, Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp.341-345.
[9]Kevin W. Bowyer, Karen Hollingswortha, and Patrick J. Flynna, Image understanding for iris biometrics:A survey [J], Computer Vision and Image Understanding Vol.110,2008, pp.281-307.
[10]Hadi Farzin, Hamid Abrishami-Moghaddam, and Mohammad-Shahram Moin, A Novel Retinal Identification System [J], Journal on Advances in Signal Processing, Vol.2008.
[11]Jie Wu, Zhengding Qiu, and Dongmei Sun, A hierarchical identification method based on improved hand geometry and regional content feature for low resolution hand images [J], Signal Processing, Vol.88,2008, pp.1447-1460.
[12]Adams Kong, David Zhang and Mohamed Kamel, A survey of palmprint recognition [J], Pattern Recognition, Volume 42, Issue 7, July 2009, pp.1408-1418.
[13]Jonas T. Kaplan, Lisa Aziz-Zadeh, Lucina Q. Uddin and Marco Iacoboni, The self across the senses:an fMRI study of self-face and self-voice recognition [J], Oxford Journals Medicine Social Cognitive & Affective Neurosci,2008, Vol.3, pp.218-223.
[14]Eui Chul Lee, Hyeon Chang Lee, Kang Ryoung Park, Finger vein recognition using minutia-based alignment and local binary pattern-based feature extraction [J], International Journal of Imaging Systems and Technology,2009, Vol.19, pp,179-186.
[15]Chatchawal Wongchoosuk, Mario Lutz and Teerakiat Kerdcharoen, Detection and Classification of Human Body Odor Using an Electronic Nose [J], Sensors,2009, Vol.9, pp.7234-7249.
[16]Christian Micheloni, Sergio Canazza and Gian Luca Foresti, Audio-video biometric recognition for non-collaborative access granting [J], Journal of Visual Languages & Computing, Vol.20,2009, pp.353-367.
[17]Ping Yan, Kevin W. Bowyer, Biometric Recognition Using 3D Ear Shape [J], IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, Vol.29, No.8, pp.1297-1308.
[18]Marcos Faundez-Zanuy, On-line signature recognition based on VQ-DTW [J], Pattern Recognition,2007, Vol.40, pp.981-992.
[19]Saevanee H., Bhattarakosol P., Authenticating User Using Keystroke Dynamics and Finger Pressure [G], IEEE Consumer Communications and Networking Conference,2009.
[20]Global Biometrics Technology Market (2010-2015)-Market Forecast by Products, End-User Application and Geography [R].
[21]国家自然科学基金“十一五”发展规划[R].
[22]孙冬梅,裘正定,生物特征识别技术综述[J],电子学报,2001,Vo1.29,pp.1744-1748.
[23]卢官明,李海波,刘莉,生物特征识别综述[J],南京邮电大学学报自然科学版,2007,Vol.27,pp.81-88.
[24]Leonard A. Jackson, Biometric technology:the future of identity assurance and authentication in the lodging industry [J], International Journal of Contemporary Hospitality Management, Vol.21, pp.892-905.
[25]Anil Jain, Lin Hong, Sharath Pankanti, Biometric identification [M], Communications of the ACM,2000.
[26]A. K Jain, A. Ross, S. Pankanti, Biometrics:a tool for information security [J], IEEE Transactions on Information Forensics and Security, 2006, Vol.1, pp.125-143.
[27]田捷, 杨鑫, 生物特征识别技术前景广阔[J], 自动识别技术与应用,2004, Vol.1.
[28]J. L. Wayman, A. K. Jain, D. Maltoni and D. Maio, Biometric Systems Technology [M], Design and Performance Evaluation, Springer,2005.
[29]林喜荣, 黄析伟, 苏晓生, 周斌, 戴晓清, 生物特征识别技术的标准化进程[J], 清华大学学报自然科学版,2006, Vol.46, pp.194-198.
[30]张敏贵,周德龙,潘泉,张洪才,生物特征识别及研究现状[J],生物物理学报,2002,Vol.18,pp.156-161.
[31]M. Faundez-Zanuy, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez, Multimodal biometric databases:an overview [J], IEEE Aerospace and Electronic Systems Magazine,2006, Vol.21, pp.29-37.
[32]D. Maio and L. Nanni, An efficient fingerprint verification system using integrated Gabor filters and Parzen Window Classifier, NeuroComputing,2005, vol.68,, pp.208-216.
[33]田捷, 陈新建, 张阳阳, 杨鑫, 何余良, 李亮, 谢卫华, 郑志鹏,指纹识别技术的新进展[J], 自然科学进展,2006,Vol.16.,pp.400-408.
[34]何孝富, 活体虹膜识别的关键技术研究[D], 上海交通大学博士论文,2007.
[35]田启川,张润生,生物特征识别综述[J],计算机应用研究,2009,Vol.26, pp.4401-4410.
[36]顾理,庄镇泉,郑光勇,王再见,基于特征融合的手形匹配算法[J],计算机应用,2005,Vol.10.
[37]L. Nanni and A. Lumini, On selecting Gabor features for biometric authentication [J], International Journal of Computer Applications in Technology,2009, Vol.35, pp.23-28.
[38]王瑜,穆志纯,徐正光,多模态生物特征识别技术进展综述[J],2009,Vol.2.
[39]Jia Cui, Jian-Ping Li, Xiao-Jun Lu, Study on Multi-Biometric Feature Fusion and Recognition Model [C], International Conference on Apperceiving Computing and Intelligence Analysis,2008, pp.66-69.
[40]J. Kiltter, N. Poh, Biometrics:Theory, Applications and Systems [C], International Conference on BTAS 2008, pp.1-6.
[41]张志坚,多模态生物特征识别融合算法的研究[D], 中国科技大学博士论文,2008.
[42]P. Jonathon Phillips, Patrick J. Flynn, J. Ross Beveridge, W. Todd Scruggs, Alice J.O'Toole, David Bolme, Kevin W. Bowyer, Bruce A. Draper, Geof H. Givens and Yui Man Lui, Overview of the Multiple Biometrics Grand Challenge [R], Lecture Notes in Computer Science,2009, Vol.5558, pp.705-714.
[43]L. Nanni, A. Lumini and S. Brahnam, Likelihood ratio based features for a trained biometric score fusion [J], Expert Systems With Applications,2011, Vol.38, pp.58-63.
[44]《国家中长期科学和技术发展规划纲要(2006-2020年)》
[45]Stan Z. Li, Jianhuang Lai, Tieniu Tan, Guocan Feng, Yunhong Wang, Advances in Biometric Person Authentication, Lecture Notes in Computer Science, Vol.3338,Springer,2004.
[46]Yunxin Wang, Tiegen Liu, and Junfeng Jiang, A multi-resolution wavelet algorithm for hand vein pattern recognition [J], Chinese Optics Letters,2008, Vol.6, pp.657-660.
[47]Lingyu Wang, Graham Leedham, and David Siu-Yeung Cho, Minutiae feature analysis for infrared hand vein pattern biometrics [J], Pattern Recognition,2008,Vol.41, March, pp.920-929.
[48]Li Xueyan and Guo Shuxu, The Fourth Biometric-Vein Recognition, Pattern Recognition Techniques, Technology and Applications [M].
[49]Lin Wanga, Mo Daib, Application of a new type of singular points in fingerprint classification [J], Pattern Recognition Letters,2007, Vol.28, pp.1640-1650.
[50]李永,殷建平,祝恩,胡春风,陈晖,多指纹识别比较研究[J],计算机工程与科学,2008, Vol.30, pp.32-35.
[51]R. Cappelli, FVC:Fingerprint Verification Competitions, Second BSI-Symposium on Biometrics,2004, pp.56-63.
[52]Miyuki Kono, Hironori Ueki, and Shin-ichiro Umemura, Near-Infrared Finger Vein Patterns for Personal Identification [J], Applied Optics, 2002, Vol.41, pp.7429-7436.
[53]D. Maltoni, Generation of Synthetic Fingerprint Image Databases, in N. Ratha and R. Bolle, Automatic Fingerprint Recognition Systems, Springer,2004.
[54]余成波, 秦华锋, 生物特征识别技术：手指静脉识别技术[M], 清华大学出版社,2009.
[55]田捷,杨鑫, 生物特征识别理论与应用[M],清华大学出版社,2009.
[56]李强,手部特征识别及特征级融合算法研究[D],北京交通大学博士论文,2006.
[57]王志芳,基于感知信息的多模态生物特征融合技术研究[D],哈尔滨工业大学博士论文,2009.
[58]TAO Hong yan, ZHANG Rui, YU Chengbo, The Optimization Design for Biometic Features Combination in Multimodal Biometrics [J], Piezoelectrics & Acoustooptics.
[59]何友, 彭应宁, 陆大, 多传感器数据融合模型综述[J], 清华大学学报(自然科学版),1996,Vol.9.
[60]朱泽君, 黄涛, 刘曦霞, 吕杨, 多传感器数据融合技术研究现状及发展方向[J], 舰船电子工程,2009, Vol 29, pp.13-16.
[61]CJ. Watson, CL. Wilson, Fingerprint Database, National Insititute of Standards and Technology Advanced Systems Division Image Recognition Group,1992.
[62]Optel Inc. http://www.optel.pl/software/english/synt.htm
[63]Sergey O. Novikov and Gennady N. Glushchenko, Fingerprint ridge structure generation models,1998, Proc. SPIE 3346.
[64]R. Cappelli, D. Maio and D. Maltoni, An Improved Noise Model for the Generation of Synthetic Fingerprints, Eighth International Conference on Control, Automation, Robotics and Vision (ICARCV2004), Kunming, China,2004, Vol.2, pp.1250-1255.
[65]胡瑾,田捷,陈新建,杨鑫,时鹏,一种指纹合成的方法及其实现[J],软件学报,2007, Vol.18, pp.517-526.
[66]S. N. Yanushkevich, Synthetic Biometrics:A Survey [C], International Joint Conference on Neural Networks,2006,676-683.
[67]Lingyu Wang, Graham Leedham, Near- and Far- Infrared Imaging for Vein Pattern Biometrics [C],2006 IEEE International Conference on Advanced Video and Signal Based Surveillance, pp.52.
[68]S. Crisan, I.G. Tarnovan, T. E. Crisan, A Low Cost Vein Detection System Using Near Infrared Radiation [C], Sensors Applications Symposium,2007, pp.1-6.
[69]李雪妍, 融合指纹和指静脉的多模态生物识别技术的研究[D], 吉林大学博士论文,2008.
[70]毋河海,S形分布的数据拟合数学模型研究[J]武汉大学学报(信息科学版),2009, Vol.34.
[71]蔡山, 张浩, 陈洪辉, 沙基昌, 基于最小二乘法的分段三次曲线拟合方法研究[J], 科学技术与工程,2007, Vol.7, pp.352-355.
[72]张亮, 指纹图像传感器技术关键及发展趋势[J], 传感器技术,2005,Vol.24, pp.1-3.
[73]李俊, 吴怀宇, 李腾飞, 艾峥, 赵新, 指纹图像采集系统的设计与实现[J], 传感器技术,2005,Vol.24,No.1,pp.38-39.
[74]Arun Ross and Anil Jain, Biometric Sensor Interoperability:A Case Study in Fingerprints [R], Lecture Notes in Computer Science,2004, Vol.3087, pp.134-145.
[75]尤政,孙文泱,蓝强,基于微光学元件的指纹图像传感器实验研究[C],第四届全国微米/纳米技术学术会议,2000, Vol.4.
[76]黄玮, 韩正臣, 多指指纹采集仪的光学系统设计[J],光学精密工程,2006, Vol.14, No.6, pp.955-958.
[77]北图高科公司,http://www.pkuimage.com/
[78]http://news.sina.com.cn/o/2008-06-22/102914055917s.shtml
[79]Davide Maltoni, Dario Maio, Anil K. Jain, Salil Prabhakar, Handbook of Fingerprint Recognition[M], Springer,2009.
[80]刘金根,一种基于现场定标的光电图像畸变校正算法[J], 光子学报,2004,Vol.33,No.6,pp.732-735.
[81]Ralph Weissleder, Ching-Hsuan Tung, Umar Mahmood, and Alexei Bogdanov Jr, In vivo imaging of tumors with protease-activated near-infrared fluorescent probes[J], NATURE BIOTECHNOLOGY,1999, Vol.17, pp.375-378.
[82]John V Frangioni, In vivo near-infrared fluorescence imaging[J], Current Opinion in Chemical Biology,2003, Vol.7, No.5, pp.626-634.
[83]Tan XJ, Bhanu B, Lin YQ, Fingerprint classification based on learned features[J], IEEE Trans. on Systems, Man, and Cybernetics,2005, Vol.35, No.3, pp.287-300.
[84]Bhanu B, Tan XJ, Fingerprint indexing based on novel features of minutiae triplets[J], IEEE Trans. on Pattern Analysis and Machine Intelligence,2003, Vol.25, No.5, pp.616-622.
[85]Li J, Wang H, Fingerprint indexing based on symmetrical measurement, The 18th International Conf. on Pattern Recognition, Washington:IEEE Computer Society,2006, pp.1038-1041.
[86]时鹏, 田捷, 苏琪, 基于奇异点邻近结构的快速指纹识别[J], 软件学报,2008,Vol.19, No.12, pp.3134-3146.
[87]K.Rao, K. Balck, Type Classification of Fingerprints:A Syntactic Approach, IEEE Trans. Pattern Analysis and Machine Intelligence,1980, Vol.2, pp.223-231.
[88]K. Karu, A.K.Jain, Fingerprint Classification, Pattern Recognition, 1996, Vol.29, No.3, pp.389-404.
[89]Mehran Yazdi, and Kazem Gheysari, A New Approach for the Fingerprint Classification Based on Gray-Level Co-Occurrence Matrix[J], International Journal of Computer and Information Science and Engineering,2008, Vol.23, pp.171-174.
[90]Yi Wang, Jiankun Hu, Damien Phillips, A Fingerprint Orientation Model Based on 2D Fourier Expansion (FOMFE) and Its Application to Singular-Point Detection and Fingerprint Indexing, IEEE Transactions on Pattern Analysis and Machine Intelligence,2007, Vol.29, No.4, pp.573-585.
[91]Jun Lia, Wei-Yun Yaub and Han Wang, Combining singular points and orientation image information for fingerprint classification, Pattern Recognition,2008, Vol.41, Issuel, pp.353-366.
[92]Fadzilah Ahmad, Dzulkifli Mohamad, A Review on Fingerprint Classification Techniques[C],2009, International Conference on Computer Technology and Development, Vol.2, pp.411-415.
[93]Xiangrong Li, Guohui Wang, Xiangjiang Lu, Neural Network Based Automatic Fingerprints Classification Algorithm,2010 International Conference of Information Science and Management Engineering, vol.1, pp.94-96.
[94]Feng Wang, Yun Chen, Hao Wang, Xiu-you Wang, Fingerprint Classification Based on Improved Singular Points Detection and Central Symmetrical Axis[C], International Conference on Artificial Intelligence and Computational Intelligence,2009, Vol.3, pp.508-512.
[95]Anne M. P. Canuto, Fernando Pintro, Antonino Feitosa Neto, Michael C. Fairhurst, Enhancing Performance of Cancellable Fingerprint Biometrics Using Classifier Ensembles[C],2010, pp.55-60.
[96]Wei Liu, Yonghui Chen, Fang Wan, Fingerprint Classification by Ridgeline and Singular Point Analysis[J], Congress on Image and Signal Processing,2008, Vol.4, pp.594-598.
[97]宋德铮,林喜荣,肖立宏,利用中心点信息的活体指纹分类算法[J],电子技术应用,2004, Vol.2, pp.11-14.
[98]Neil Yager, Adnan Amin, Fingerprint Classification:a review[M], 2004, Springer-Verlag.
[99]王科俊,丁宇航,庄大燕, 王大振, 手背静脉图像阈值分割.自动化技术与应用,2005.24(8)：p.19-22.
[100]唐远炎, 王玲, 小波分析与文本文字识别.科学出版社,2004.第一版.
[101]Miura, N., A. Nagasaka, T. Miyatake, Feature extraction of fingervein patterns based on repeated line tracking and its application to personal identification, Machine Vision and Applications,2004, Vol.15, No.4, pp.194-203.
[102]Naoto MIURA, Akio NAGASAKA, Takafumi MIYATAKE, Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles. The Institute of Electronics, Information and Communication Engineers, 2007.90(8):p.1185-1194.
[103]郑丹,不完整指纹图像宏观特征的提取与确定,吉林大学硕士论文,2004.
[104]王云新, 刘铁根, 朱均超, 霍晓飞, 江俊峰, 嵌入式人体手背静脉图像采集系统的研制[J], 仪器仪表学报,2009, Vol.30, No.2,308-312.
[2]V. Roman, Yampolskiy, and Venu Govindaraju, Behavioural biometrics: a survey and classification [J], International Journal of Biometrics, Vol.1, No.1,2008, pp.81-113.
[3]A. K. Jain, Biometric Recognition:Overview and Recent Advances, Lecture Notes in Computer Science[R],2007, Vol.4756, pp.13-19.
[4]Stan Z. Li, Ben Schouten, Massimo Tistarelli, Biometrics at a Distance:Issues, Challenges, and Prospects [M], Springer,2009.
[5]Massimo Tistarelli,3D Face Recognition:Technology and Applications [M], Springer,2009.
[6]Yoshida Kazuhiko, Honma Shota, Ohtsuka Tomohiko, Aoki Hiroyuki, New Fingerprint Minutiae Extraction Using Ridge Flux Analysis [C], Asia Pacific Signal and Information Processing Association,2009.
[7]Jianjiang Feng, Combining minutiae descriptors for fingerprint matching [J], Pattern Recognition, Vol.41,2008, pp.342-352.
[8]Haiyun Xu, Raymond N.J., Spectral Minutiae Representations for Fingerprint Recognition [C],2010, Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp.341-345.
[9]Kevin W. Bowyer, Karen Hollingswortha, and Patrick J. Flynna, Image understanding for iris biometrics:A survey [J], Computer Vision and Image Understanding Vol.110,2008, pp.281-307.
[10]Hadi Farzin, Hamid Abrishami-Moghaddam, and Mohammad-Shahram Moin, A Novel Retinal Identification System [J], Journal on Advances in Signal Processing, Vol.2008.
[11]Jie Wu, Zhengding Qiu, and Dongmei Sun, A hierarchical identification method based on improved hand geometry and regional content feature for low resolution hand images [J], Signal Processing, Vol.88,2008, pp.1447-1460.
[12]Adams Kong, David Zhang and Mohamed Kamel, A survey of palmprint recognition [J], Pattern Recognition, Volume 42, Issue 7, July 2009, pp.1408-1418.
[13]Jonas T. Kaplan, Lisa Aziz-Zadeh, Lucina Q. Uddin and Marco Iacoboni, The self across the senses:an fMRI study of self-face and self-voice recognition [J], Oxford Journals Medicine Social Cognitive & Affective Neurosci,2008, Vol.3, pp.218-223.
[14]Eui Chul Lee, Hyeon Chang Lee, Kang Ryoung Park, Finger vein recognition using minutia-based alignment and local binary pattern-based feature extraction [J], International Journal of Imaging Systems and Technology,2009, Vol.19, pp,179-186.
[15]Chatchawal Wongchoosuk, Mario Lutz and Teerakiat Kerdcharoen, Detection and Classification of Human Body Odor Using an Electronic Nose [J], Sensors,2009, Vol.9, pp.7234-7249.
[16]Christian Micheloni, Sergio Canazza and Gian Luca Foresti, Audio-video biometric recognition for non-collaborative access granting [J], Journal of Visual Languages & Computing, Vol.20,2009, pp.353-367.
[17]Ping Yan, Kevin W. Bowyer, Biometric Recognition Using 3D Ear Shape [J], IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, Vol.29, No.8, pp.1297-1308.
[18]Marcos Faundez-Zanuy, On-line signature recognition based on VQ-DTW [J], Pattern Recognition,2007, Vol.40, pp.981-992.
[19]Saevanee H., Bhattarakosol P., Authenticating User Using Keystroke Dynamics and Finger Pressure [G], IEEE Consumer Communications and Networking Conference,2009.
[20]Global Biometrics Technology Market (2010-2015)-Market Forecast by Products, End-User Application and Geography [R].
[21]国家自然科学基金“十一五”发展规划[R].
[22]孙冬梅,裘正定,生物特征识别技术综述[J],电子学报,2001,Vo1.29,pp.1744-1748.
[23]卢官明,李海波,刘莉,生物特征识别综述[J],南京邮电大学学报自然科学版,2007,Vol.27,pp.81-88.
[24]Leonard A. Jackson, Biometric technology:the future of identity assurance and authentication in the lodging industry [J], International Journal of Contemporary Hospitality Management, Vol.21, pp.892-905.
[25]Anil Jain, Lin Hong, Sharath Pankanti, Biometric identification [M], Communications of the ACM,2000.
[26]A. K Jain, A. Ross, S. Pankanti, Biometrics:a tool for information security [J], IEEE Transactions on Information Forensics and Security, 2006, Vol.1, pp.125-143.
[27]田捷, 杨鑫, 生物特征识别技术前景广阔[J], 自动识别技术与应用,2004, Vol.1.
[28]J. L. Wayman, A. K. Jain, D. Maltoni and D. Maio, Biometric Systems Technology [M], Design and Performance Evaluation, Springer,2005.
[29]林喜荣, 黄析伟, 苏晓生, 周斌, 戴晓清, 生物特征识别技术的标准化进程[J], 清华大学学报自然科学版,2006, Vol.46, pp.194-198.
[30]张敏贵,周德龙,潘泉,张洪才,生物特征识别及研究现状[J],生物物理学报,2002,Vol.18,pp.156-161.
[31]M. Faundez-Zanuy, J. Fierrez-Aguilar, J. Ortega-Garcia, J. Gonzalez-Rodriguez, Multimodal biometric databases:an overview [J], IEEE Aerospace and Electronic Systems Magazine,2006, Vol.21, pp.29-37.
[32]D. Maio and L. Nanni, An efficient fingerprint verification system using integrated Gabor filters and Parzen Window Classifier, NeuroComputing,2005, vol.68,, pp.208-216.
[33]田捷, 陈新建, 张阳阳, 杨鑫, 何余良, 李亮, 谢卫华, 郑志鹏,指纹识别技术的新进展[J], 自然科学进展,2006,Vol.16.,pp.400-408.
[34]何孝富, 活体虹膜识别的关键技术研究[D], 上海交通大学博士论文,2007.
[35]田启川,张润生,生物特征识别综述[J],计算机应用研究,2009,Vol.26, pp.4401-4410.
[36]顾理,庄镇泉,郑光勇,王再见,基于特征融合的手形匹配算法[J],计算机应用,2005,Vol.10.
[37]L. Nanni and A. Lumini, On selecting Gabor features for biometric authentication [J], International Journal of Computer Applications in Technology,2009, Vol.35, pp.23-28.
[38]王瑜,穆志纯,徐正光,多模态生物特征识别技术进展综述[J],2009,Vol.2.
[39]Jia Cui, Jian-Ping Li, Xiao-Jun Lu, Study on Multi-Biometric Feature Fusion and Recognition Model [C], International Conference on Apperceiving Computing and Intelligence Analysis,2008, pp.66-69.
[40]J. Kiltter, N. Poh, Biometrics:Theory, Applications and Systems [C], International Conference on BTAS 2008, pp.1-6.
[41]张志坚,多模态生物特征识别融合算法的研究[D], 中国科技大学博士论文,2008.
[42]P. Jonathon Phillips, Patrick J. Flynn, J. Ross Beveridge, W. Todd Scruggs, Alice J.O'Toole, David Bolme, Kevin W. Bowyer, Bruce A. Draper, Geof H. Givens and Yui Man Lui, Overview of the Multiple Biometrics Grand Challenge [R], Lecture Notes in Computer Science,2009, Vol.5558, pp.705-714.
[43]L. Nanni, A. Lumini and S. Brahnam, Likelihood ratio based features for a trained biometric score fusion [J], Expert Systems With Applications,2011, Vol.38, pp.58-63.
[44]《国家中长期科学和技术发展规划纲要(2006-2020年)》
[45]Stan Z. Li, Jianhuang Lai, Tieniu Tan, Guocan Feng, Yunhong Wang, Advances in Biometric Person Authentication, Lecture Notes in Computer Science, Vol.3338,Springer,2004.
[46]Yunxin Wang, Tiegen Liu, and Junfeng Jiang, A multi-resolution wavelet algorithm for hand vein pattern recognition [J], Chinese Optics Letters,2008, Vol.6, pp.657-660.
[47]Lingyu Wang, Graham Leedham, and David Siu-Yeung Cho, Minutiae feature analysis for infrared hand vein pattern biometrics [J], Pattern Recognition,2008,Vol.41, March, pp.920-929.
[48]Li Xueyan and Guo Shuxu, The Fourth Biometric-Vein Recognition, Pattern Recognition Techniques, Technology and Applications [M].
[49]Lin Wanga, Mo Daib, Application of a new type of singular points in fingerprint classification [J], Pattern Recognition Letters,2007, Vol.28, pp.1640-1650.
[50]李永,殷建平,祝恩,胡春风,陈晖,多指纹识别比较研究[J],计算机工程与科学,2008, Vol.30, pp.32-35.
[51]R. Cappelli, FVC:Fingerprint Verification Competitions, Second BSI-Symposium on Biometrics,2004, pp.56-63.
[52]Miyuki Kono, Hironori Ueki, and Shin-ichiro Umemura, Near-Infrared Finger Vein Patterns for Personal Identification [J], Applied Optics, 2002, Vol.41, pp.7429-7436.
[53]D. Maltoni, Generation of Synthetic Fingerprint Image Databases, in N. Ratha and R. Bolle, Automatic Fingerprint Recognition Systems, Springer,2004.
[54]余成波, 秦华锋, 生物特征识别技术：手指静脉识别技术[M], 清华大学出版社,2009.
[55]田捷,杨鑫, 生物特征识别理论与应用[M],清华大学出版社,2009.
[56]李强,手部特征识别及特征级融合算法研究[D],北京交通大学博士论文,2006.
[57]王志芳,基于感知信息的多模态生物特征融合技术研究[D],哈尔滨工业大学博士论文,2009.
[58]TAO Hong yan, ZHANG Rui, YU Chengbo, The Optimization Design for Biometic Features Combination in Multimodal Biometrics [J], Piezoelectrics & Acoustooptics.
[59]何友, 彭应宁, 陆大, 多传感器数据融合模型综述[J], 清华大学学报(自然科学版),1996,Vol.9.
[60]朱泽君, 黄涛, 刘曦霞, 吕杨, 多传感器数据融合技术研究现状及发展方向[J], 舰船电子工程,2009, Vol 29, pp.13-16.
[61]CJ. Watson, CL. Wilson, Fingerprint Database, National Insititute of Standards and Technology Advanced Systems Division Image Recognition Group,1992.
[62]Optel Inc. http://www.optel.pl/software/english/synt.htm
[63]Sergey O. Novikov and Gennady N. Glushchenko, Fingerprint ridge structure generation models,1998, Proc. SPIE 3346.
[64]R. Cappelli, D. Maio and D. Maltoni, An Improved Noise Model for the Generation of Synthetic Fingerprints, Eighth International Conference on Control, Automation, Robotics and Vision (ICARCV2004), Kunming, China,2004, Vol.2, pp.1250-1255.
[65]胡瑾,田捷,陈新建,杨鑫,时鹏,一种指纹合成的方法及其实现[J],软件学报,2007, Vol.18, pp.517-526.
[66]S. N. Yanushkevich, Synthetic Biometrics:A Survey [C], International Joint Conference on Neural Networks,2006,676-683.
[67]Lingyu Wang, Graham Leedham, Near- and Far- Infrared Imaging for Vein Pattern Biometrics [C],2006 IEEE International Conference on Advanced Video and Signal Based Surveillance, pp.52.
[68]S. Crisan, I.G. Tarnovan, T. E. Crisan, A Low Cost Vein Detection System Using Near Infrared Radiation [C], Sensors Applications Symposium,2007, pp.1-6.
[69]李雪妍, 融合指纹和指静脉的多模态生物识别技术的研究[D], 吉林大学博士论文,2008.
[70]毋河海,S形分布的数据拟合数学模型研究[J]武汉大学学报(信息科学版),2009, Vol.34.
[71]蔡山, 张浩, 陈洪辉, 沙基昌, 基于最小二乘法的分段三次曲线拟合方法研究[J], 科学技术与工程,2007, Vol.7, pp.352-355.
[72]张亮, 指纹图像传感器技术关键及发展趋势[J], 传感器技术,2005,Vol.24, pp.1-3.
[73]李俊, 吴怀宇, 李腾飞, 艾峥, 赵新, 指纹图像采集系统的设计与实现[J], 传感器技术,2005,Vol.24,No.1,pp.38-39.
[74]Arun Ross and Anil Jain, Biometric Sensor Interoperability:A Case Study in Fingerprints [R], Lecture Notes in Computer Science,2004, Vol.3087, pp.134-145.
[75]尤政,孙文泱,蓝强,基于微光学元件的指纹图像传感器实验研究[C],第四届全国微米/纳米技术学术会议,2000, Vol.4.
[76]黄玮, 韩正臣, 多指指纹采集仪的光学系统设计[J],光学精密工程,2006, Vol.14, No.6, pp.955-958.
[77]北图高科公司,http://www.pkuimage.com/
[78]http://news.sina.com.cn/o/2008-06-22/102914055917s.shtml
[79]Davide Maltoni, Dario Maio, Anil K. Jain, Salil Prabhakar, Handbook of Fingerprint Recognition[M], Springer,2009.
[80]刘金根,一种基于现场定标的光电图像畸变校正算法[J], 光子学报,2004,Vol.33,No.6,pp.732-735.
[81]Ralph Weissleder, Ching-Hsuan Tung, Umar Mahmood, and Alexei Bogdanov Jr, In vivo imaging of tumors with protease-activated near-infrared fluorescent probes[J], NATURE BIOTECHNOLOGY,1999, Vol.17, pp.375-378.
[82]John V Frangioni, In vivo near-infrared fluorescence imaging[J], Current Opinion in Chemical Biology,2003, Vol.7, No.5, pp.626-634.
[83]Tan XJ, Bhanu B, Lin YQ, Fingerprint classification based on learned features[J], IEEE Trans. on Systems, Man, and Cybernetics,2005, Vol.35, No.3, pp.287-300.
[84]Bhanu B, Tan XJ, Fingerprint indexing based on novel features of minutiae triplets[J], IEEE Trans. on Pattern Analysis and Machine Intelligence,2003, Vol.25, No.5, pp.616-622.
[85]Li J, Wang H, Fingerprint indexing based on symmetrical measurement, The 18th International Conf. on Pattern Recognition, Washington:IEEE Computer Society,2006, pp.1038-1041.
[86]时鹏, 田捷, 苏琪, 基于奇异点邻近结构的快速指纹识别[J], 软件学报,2008,Vol.19, No.12, pp.3134-3146.
[87]K.Rao, K. Balck, Type Classification of Fingerprints:A Syntactic Approach, IEEE Trans. Pattern Analysis and Machine Intelligence,1980, Vol.2, pp.223-231.
[88]K. Karu, A.K.Jain, Fingerprint Classification, Pattern Recognition, 1996, Vol.29, No.3, pp.389-404.
[89]Mehran Yazdi, and Kazem Gheysari, A New Approach for the Fingerprint Classification Based on Gray-Level Co-Occurrence Matrix[J], International Journal of Computer and Information Science and Engineering,2008, Vol.23, pp.171-174.
[90]Yi Wang, Jiankun Hu, Damien Phillips, A Fingerprint Orientation Model Based on 2D Fourier Expansion (FOMFE) and Its Application to Singular-Point Detection and Fingerprint Indexing, IEEE Transactions on Pattern Analysis and Machine Intelligence,2007, Vol.29, No.4, pp.573-585.
[91]Jun Lia, Wei-Yun Yaub and Han Wang, Combining singular points and orientation image information for fingerprint classification, Pattern Recognition,2008, Vol.41, Issuel, pp.353-366.
[92]Fadzilah Ahmad, Dzulkifli Mohamad, A Review on Fingerprint Classification Techniques[C],2009, International Conference on Computer Technology and Development, Vol.2, pp.411-415.
[93]Xiangrong Li, Guohui Wang, Xiangjiang Lu, Neural Network Based Automatic Fingerprints Classification Algorithm,2010 International Conference of Information Science and Management Engineering, vol.1, pp.94-96.
[94]Feng Wang, Yun Chen, Hao Wang, Xiu-you Wang, Fingerprint Classification Based on Improved Singular Points Detection and Central Symmetrical Axis[C], International Conference on Artificial Intelligence and Computational Intelligence,2009, Vol.3, pp.508-512.
[95]Anne M. P. Canuto, Fernando Pintro, Antonino Feitosa Neto, Michael C. Fairhurst, Enhancing Performance of Cancellable Fingerprint Biometrics Using Classifier Ensembles[C],2010, pp.55-60.
[96]Wei Liu, Yonghui Chen, Fang Wan, Fingerprint Classification by Ridgeline and Singular Point Analysis[J], Congress on Image and Signal Processing,2008, Vol.4, pp.594-598.
[97]宋德铮,林喜荣,肖立宏,利用中心点信息的活体指纹分类算法[J],电子技术应用,2004, Vol.2, pp.11-14.
[98]Neil Yager, Adnan Amin, Fingerprint Classification:a review[M], 2004, Springer-Verlag.
[99]王科俊,丁宇航,庄大燕, 王大振, 手背静脉图像阈值分割.自动化技术与应用,2005.24(8)：p.19-22.
[100]唐远炎, 王玲, 小波分析与文本文字识别.科学出版社,2004.第一版.
[101]Miura, N., A. Nagasaka, T. Miyatake, Feature extraction of fingervein patterns based on repeated line tracking and its application to personal identification, Machine Vision and Applications,2004, Vol.15, No.4, pp.194-203.
[102]Naoto MIURA, Akio NAGASAKA, Takafumi MIYATAKE, Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles. The Institute of Electronics, Information and Communication Engineers, 2007.90(8):p.1185-1194.
[103]郑丹,不完整指纹图像宏观特征的提取与确定,吉林大学硕士论文,2004.
[104]王云新, 刘铁根, 朱均超, 霍晓飞, 江俊峰, 嵌入式人体手背静脉图像采集系统的研制[J], 仪器仪表学报,2009, Vol.30, No.2,308-312.
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