指纹自动识别系统的算法研究
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摘要
出于安全性和方便性的考虑，生物以别技术得到越来越多的重视，其中，指纹自动识别系统是当前最热门的应用，这是山于指纹采集方便，且具有唯一性。本文利用计算机和活体指纹录入仪，综合利用图像处理和模式识别技术，对活体指纹识别系统所应用的各种技术进行了探讨，描述了一个指纹识别系统的一整套实现方案，并提出了一些自己的观点。全文内容共分为六章：第一章为绪论；第二章为系统设计；第三章为指纹图像细节特征提取，包括指纹图像与背景分离、指纹图像增强和二值化、细线化、提取指纹细节特征点；第四章为指纹图像匹配，这里介绍了点模式匹配通常方法和对其的改进；第五章为本自动指纹识别系统的实验结果；第六章为结论部分。主要研究内容为：1 在指纹图像与背景分割部分，在采用方筹法后，利用相邻的分割结果信息确定指纹范围。2 在指纹增强和二值化部分，利用块方向图滤波的连接断线和分离粘连的特点，点方向图滤波对细节点精确的特点，把二者结合起来，使得二值化效果有明显改进。3 提取指纹特征点后，采用设定的几个规则去除伪特征点。4 在指纹图像匹配部分对点模式匹配方法进行了改进，使得匹配所需时间缩短。
本文较为系统地研究了自动指纹识别的理论和技术，在指纹图象方向信息提取和利用指纹图象方向信息提取指纹脊线方面的研究有所创新。本文可以为指纹技术人员的研究提供参考。
More and more people pay attention to Biology identification technology for the security and convenience reason. Fingerprint recognition is the most important application of it. That is because that it is easy to get the fingerprint of someone you want and there is no same fingerprint in the world. Based on computer and live fingerprint scanner, using technology image processing and pattern recognition, this study investigates theory and methods of automatic fingerprint identification, implements algorithms of automatic fingerprint identification system(AFIS). The thesis is organized as follows. Chapter 1 is introduction. Chapter 2 is presents design of the automatic fingerprint identification system and related issues. Chapter 3 discusses fingerprint feature extraction and a new minutiae algorithm based on imperfect thinning fingerprint image. Chapter 4 deals with a minutiae matching algorithm based on point pattern matching. The last Chapter is conchision. The main contents are as follow:
1 The method to segment fingerprint from background are studied. By selecting threshold which makes the number of pixels that are bigger than the threshold equal to the number of pixels that are smaller than it for local area. ,fingerprint image can be self-adaptively segmented from the background. After that we can make sure the final result through the information around the local area.
2 The method of ridge extraction is studied. Using the orientation information of local area, masks for smoothing and enhancing are designed respectively. These masks can smooth the image along orientation of the ridges and enhance the image along orientation orthogonal to ridges at the same time. Results indicate that the method can connect breaks of the ridges and can dispart conglutinated ridges. As a result, the ridges that are single color are extracted correctly.
3 After get the minutiaes from thinning ridges, erase some minutiaes that are not real minutiaes using several regulars.
4 Improve the point pattern matching method to reduce the spending on time.
This study systemically investigates theory and methods of automatic fingerprint identification, bring a new idea in acquiring minutiae extraction with accuracy.This study will be helpful for the people who relate with AFIS.
本文较为系统地研究了自动指纹识别的理论和技术，在指纹图象方向信息提取和利用指纹图象方向信息提取指纹脊线方面的研究有所创新。本文可以为指纹技术人员的研究提供参考。
More and more people pay attention to Biology identification technology for the security and convenience reason. Fingerprint recognition is the most important application of it. That is because that it is easy to get the fingerprint of someone you want and there is no same fingerprint in the world. Based on computer and live fingerprint scanner, using technology image processing and pattern recognition, this study investigates theory and methods of automatic fingerprint identification, implements algorithms of automatic fingerprint identification system(AFIS). The thesis is organized as follows. Chapter 1 is introduction. Chapter 2 is presents design of the automatic fingerprint identification system and related issues. Chapter 3 discusses fingerprint feature extraction and a new minutiae algorithm based on imperfect thinning fingerprint image. Chapter 4 deals with a minutiae matching algorithm based on point pattern matching. The last Chapter is conchision. The main contents are as follow:
1 The method to segment fingerprint from background are studied. By selecting threshold which makes the number of pixels that are bigger than the threshold equal to the number of pixels that are smaller than it for local area. ,fingerprint image can be self-adaptively segmented from the background. After that we can make sure the final result through the information around the local area.
2 The method of ridge extraction is studied. Using the orientation information of local area, masks for smoothing and enhancing are designed respectively. These masks can smooth the image along orientation of the ridges and enhance the image along orientation orthogonal to ridges at the same time. Results indicate that the method can connect breaks of the ridges and can dispart conglutinated ridges. As a result, the ridges that are single color are extracted correctly.
3 After get the minutiaes from thinning ridges, erase some minutiaes that are not real minutiaes using several regulars.
4 Improve the point pattern matching method to reduce the spending on time.
This study systemically investigates theory and methods of automatic fingerprint identification, bring a new idea in acquiring minutiae extraction with accuracy.This study will be helpful for the people who relate with AFIS.
引文
[1] ISENORD K, ZAKY S G. Fingerprint identification using graph matching[J]. Pattern Recognition, 1986, 19 (2). 113～122
[2] 王崇文，李见为，林国清等．指纹取像与指纹识别．计算机工程．2002，28(4)．10～13
[3] ANDREW K, HRECHAK, JAMES, A.Mchugh. Automated fingerprint recognition using structural matching [J]. Pattern Recognition, 1990, 23 (8).839～904
[4] WANGRun sheng. Image Understanding[M]. Changsha:National Defence Science & Technology University Press, 1995
[5] HANWei hong. Preprocessing in an Automatic Fingerprint Identifification System[J]. Computer Research & Development, 1997, 34 (12) 913～920
[6] Ratha N K. Adaptive Flow Orientation-based Feature Extraction Fingerprint Image[J]. Pattern Recognition, 1995,28 (11). 1657～1672
[7] SANJAYRANADE, AZRIELROSENFELD. Point pattern matching by relaxion[J]. Pattern Reconifion, 1980, 12. 269～275
[8] SKEAD, BARRODALE, KUWAHARAR, etc. A contral matching algorithm[J]. Pattern Recognition, 1993, 26 (2) 269～276
[9] Federal Bureau of Investigation. The Science of Fingerprint: Classification and Uses. U.S. Government Printing Office, Washington, D.C., 1984
[10] RAO A R. A taxonomy for texture description and identification[M]. New York: Springer-Verlag, 1990
[11] JAIN A K. An overview of biometrics, http://biometrics.cse.msu.edu/infor.html, 1999-07-20
[12] HONG L, JAIN A K, PANKANTI S, etc. Fingerprint image enhancement[A]. Proc. First IEEE WACV[C], Sarasota: Fla, 1996. 166～1671
[13] MICAEL M.S.CHONG, TAN HAN NGEE, LIU JUN. Geometric framework for fingerprint image classification[J]. Pattern Recognition, 1997, 30 (9).1475～1488
[14] KAWAGOE M, TOJO A. Fingerprint pattern classification[J]. Pattern Recognition, 1984, 17 (3).259～303
[15] 黄席樾，马笑潇，汪鹏等．基于方向基元集描述地求取指纹方向图的方法及应用[J]．重庆大学学报(自然科学版)，2000，23(5)．57～61
[16] 黄席樾，马笑潇，沈志熙等．基于遗传算法的神经网络指纹分析器研究[J]．重庆大学学报(自然科学版)，2001，24(1)．74～77
[17] 赵向欣．中华指纹学[M]．北京：群众出版社，1997
[18] 杜朝晖，养心，陈勇，胡福乔．基于Walsh变换检测指纹方向场的算法．上海交通大学学报，2000，34(5)．708～714
[19] 刘勇，夏德麟，晏蒲柳．指纹图像预处理．计算机应用研究，2001，第7期．78～80
[20] 刘勇，晏蒲柳，郭成城．指纹图像脊线提取．武汉大学学报(理学版)，2001，47(1)．106～110
[21] http://www.idfounder.com/puafis.php.2004-1-17
[22] 尹义龙．自动指纹识别系统研究．吉林：吉林工业大学．2000
[23] S.G.Davies. Touching big brother: How biometric technology will fuse flesh and machine.Information Technology & People, 1994, 7(4). 60～69
[24] HU Xin rong. Fingerprint Identification System and Its Application. Computer Technology Information, 1999, 12.31～35
[25] 容观澳．计算机图像处理．清华大学出版社，2000
[26] K. Asai, Y.Hoshino, Y. Kato, K. Kiji. Automatic reading and matching for single fingerprint identification. In Proc.65th Int. Ass. for Identification Conf., 1～7, Ottawa, 7, Ottawa, Canada, 1991
[27] J.Atick, P. Griffin, A. Redlich. Statistical approach to shape from shading. Reconstruction of 3D face surfaces from single 2D images, Neural Computation, 1998
[28] R Bahuguna. Fingerprint verification using hologram matched filterings. In Proc. Biometric Cons-ortium Eighth Meeting, San Jose, California, June, 1996
[29] Sanjay Ranade, Azriel Rosenfeld. Point pattern matching by relaxation. Pattern Recognition, 1980, 12 (5) .269～275
[30] Stockman G, Kopstein S, Benett S. Matching images to models for registration and object detection via clustering. IEEE Transactions on Pattern Analysis and Machine Inelligence, 1982, 4 (3) .229～241
[31] Pascual Starink J P, Bacer E.. Finding point correspondences using simulated annealing. Pattern Recognition, 1995, 28 (2) . 231～240
[32] Ratkovic J. P.. Increasing efficiency in the criminal justice system, the use of new technology for criminal identification and latent print processing. California: The Rand Corporation, 1980
[33] Liu J H, Lin C H, Osterberg J W etc. Fingerprint comparison. Ⅱ: On the development of a single fingerprint filing and searching system. Journal of Forensic Science, 1985, (27). 305～317
[34] Sparrow M K, Sparrow P J.. A topological approach to the rnatehing of single fingerprints: development of algorithms for use on rolled impressions. National Bureau of Standards Special Publication, Washington, DC., Go., Printing Office, 1985. 100～126
[35] Hrechak A K, Mchugh J A. Automated fingerprint recognition using structural matching. Pattern Recognition, 1990, 23 (8). 893～904
[36] Isenor D K, Zaky S G.. Fingerprint identification using graph matching. Pattern Recognition, 1986, 19 (2). 113～122
[37] Srdjan Sobajic, Amit Manwani, Barbastathis G.. CNS286 Project: Fingerprint Recognition. Technical Report, California Institute of Technology, 1997
[38] R Bahuguna. Fingerprint verification using hologram matched filterings. In Proc. Biometric Cons-ortium Eighth Meeting, San Jose, California, June, 1996
[39] 洪波，荣钢，黄韬．一种基于遗传算法的指纹比对算法．清华大学学报(自然科学版)，2000，41(3)．93～96
[40] A. K.Jain, S.Pankanti, S.Prabhakar, A.Ross. Recent Advances in Fingerprint Verification. The 3rd International Conference on Audio and Video-Based Person Authentication (AVBPA), Sweden, 2001, June. 182～191
[41] B. M. Mehtre, N. N. Murthy, S. Kapoor, B. Chatterjee. Segmentation of fingerprint images using the directional images. Pattern Recognition, 1995, 28. 1657～1672
[42] A. M. Bazen, S. H. Crerez. Directional field computation for fingerprints based on the principal component analysis of local gradients. Proc of ProeRISC2000, 11th Annual Workshop on Circuits, Systems and Signal Processing, Nov, 2000
[43] Lee Chih-Jen, Wang Sheng-De. Fingerprint feature extraction using Gabor filters. Electronics Letters, 1999, 35 (4) .298～290
[44] Andrew W. Senior, Ruud M.Bolle. Improved Fingerprint Matching by Distortion Removal. IEICE Transactions on Information and Systems, 2001, E84-D (7). 825～832
[45] Zhou J., Rong G., Bian ZQ., He D.. Effective algorithm for rolled fingerprint construction. Electronics Letters, 2001, 37 (8) .492～494
[46] Tico M, Saarinen J, Kuosmanen P.. Wavelet domain features for fingerprint recognition. Electronics Letters, 2001, 37 (1). 21～22
[47] Jiang XD., Ser W., Yau WY.. Detecting the fingerprint minutiae by adaptive tracing the gray-level ridge. Partern Recognition, 2001, 34 (5) .999～1013
[48] HE Di, RONG Gang, ZHOU Jie. Image Mosaicing Algorithm for Rolled Fingerprint Construction. Tsinghua Science and Technology, 2002, 7 (3) .317～321
[49] Chang JH., Fan KC.. Fingerprint ridge allocation in direct gray-scale domain. Pattern Recognition, 2001, 34 (10). 1907～1925
[50] Fumihito Arai, Toshio Fukuda. Fingerprint image sensing using micromechanical key and extraction algorithm for sensed fingerprint image. Journal of Robotics and Mechatronies, 2001, 13 (5) .458～463
[51] Chang JH., Fan KC.. A new model for fingerprint classification by ridge distribution sequences. Pattern Recognition, 2002, 35 (6) .1209～1223
[52] Prabhakar S., Jain AK.. Decision-level fusion in fingerprint verification. Pattern Recognition, 2002, 35 (4) .861～874
[53] E. Newham. The Biometric Report. SJB Services. New York, 1995
[54] 王崇文，李见为，郑治伟等．一种基于点模式匹配的指纹识别方法．重庆大学学报(自然科学版)，2002，25(6)．27～31
[2] 王崇文，李见为，林国清等．指纹取像与指纹识别．计算机工程．2002，28(4)．10～13
[3] ANDREW K, HRECHAK, JAMES, A.Mchugh. Automated fingerprint recognition using structural matching [J]. Pattern Recognition, 1990, 23 (8).839～904
[4] WANGRun sheng. Image Understanding[M]. Changsha:National Defence Science & Technology University Press, 1995
[5] HANWei hong. Preprocessing in an Automatic Fingerprint Identifification System[J]. Computer Research & Development, 1997, 34 (12) 913～920
[6] Ratha N K. Adaptive Flow Orientation-based Feature Extraction Fingerprint Image[J]. Pattern Recognition, 1995,28 (11). 1657～1672
[7] SANJAYRANADE, AZRIELROSENFELD. Point pattern matching by relaxion[J]. Pattern Reconifion, 1980, 12. 269～275
[8] SKEAD, BARRODALE, KUWAHARAR, etc. A contral matching algorithm[J]. Pattern Recognition, 1993, 26 (2) 269～276
[9] Federal Bureau of Investigation. The Science of Fingerprint: Classification and Uses. U.S. Government Printing Office, Washington, D.C., 1984
[10] RAO A R. A taxonomy for texture description and identification[M]. New York: Springer-Verlag, 1990
[11] JAIN A K. An overview of biometrics, http://biometrics.cse.msu.edu/infor.html, 1999-07-20
[12] HONG L, JAIN A K, PANKANTI S, etc. Fingerprint image enhancement[A]. Proc. First IEEE WACV[C], Sarasota: Fla, 1996. 166～1671
[13] MICAEL M.S.CHONG, TAN HAN NGEE, LIU JUN. Geometric framework for fingerprint image classification[J]. Pattern Recognition, 1997, 30 (9).1475～1488
[14] KAWAGOE M, TOJO A. Fingerprint pattern classification[J]. Pattern Recognition, 1984, 17 (3).259～303
[15] 黄席樾，马笑潇，汪鹏等．基于方向基元集描述地求取指纹方向图的方法及应用[J]．重庆大学学报(自然科学版)，2000，23(5)．57～61
[16] 黄席樾，马笑潇，沈志熙等．基于遗传算法的神经网络指纹分析器研究[J]．重庆大学学报(自然科学版)，2001，24(1)．74～77
[17] 赵向欣．中华指纹学[M]．北京：群众出版社，1997
[18] 杜朝晖，养心，陈勇，胡福乔．基于Walsh变换检测指纹方向场的算法．上海交通大学学报，2000，34(5)．708～714
[19] 刘勇，夏德麟，晏蒲柳．指纹图像预处理．计算机应用研究，2001，第7期．78～80
[20] 刘勇，晏蒲柳，郭成城．指纹图像脊线提取．武汉大学学报(理学版)，2001，47(1)．106～110
[21] http://www.idfounder.com/puafis.php.2004-1-17
[22] 尹义龙．自动指纹识别系统研究．吉林：吉林工业大学．2000
[23] S.G.Davies. Touching big brother: How biometric technology will fuse flesh and machine.Information Technology & People, 1994, 7(4). 60～69
[24] HU Xin rong. Fingerprint Identification System and Its Application. Computer Technology Information, 1999, 12.31～35
[25] 容观澳．计算机图像处理．清华大学出版社，2000
[26] K. Asai, Y.Hoshino, Y. Kato, K. Kiji. Automatic reading and matching for single fingerprint identification. In Proc.65th Int. Ass. for Identification Conf., 1～7, Ottawa, 7, Ottawa, Canada, 1991
[27] J.Atick, P. Griffin, A. Redlich. Statistical approach to shape from shading. Reconstruction of 3D face surfaces from single 2D images, Neural Computation, 1998
[28] R Bahuguna. Fingerprint verification using hologram matched filterings. In Proc. Biometric Cons-ortium Eighth Meeting, San Jose, California, June, 1996
[29] Sanjay Ranade, Azriel Rosenfeld. Point pattern matching by relaxation. Pattern Recognition, 1980, 12 (5) .269～275
[30] Stockman G, Kopstein S, Benett S. Matching images to models for registration and object detection via clustering. IEEE Transactions on Pattern Analysis and Machine Inelligence, 1982, 4 (3) .229～241
[31] Pascual Starink J P, Bacer E.. Finding point correspondences using simulated annealing. Pattern Recognition, 1995, 28 (2) . 231～240
[32] Ratkovic J. P.. Increasing efficiency in the criminal justice system, the use of new technology for criminal identification and latent print processing. California: The Rand Corporation, 1980
[33] Liu J H, Lin C H, Osterberg J W etc. Fingerprint comparison. Ⅱ: On the development of a single fingerprint filing and searching system. Journal of Forensic Science, 1985, (27). 305～317
[34] Sparrow M K, Sparrow P J.. A topological approach to the rnatehing of single fingerprints: development of algorithms for use on rolled impressions. National Bureau of Standards Special Publication, Washington, DC., Go., Printing Office, 1985. 100～126
[35] Hrechak A K, Mchugh J A. Automated fingerprint recognition using structural matching. Pattern Recognition, 1990, 23 (8). 893～904
[36] Isenor D K, Zaky S G.. Fingerprint identification using graph matching. Pattern Recognition, 1986, 19 (2). 113～122
[37] Srdjan Sobajic, Amit Manwani, Barbastathis G.. CNS286 Project: Fingerprint Recognition. Technical Report, California Institute of Technology, 1997
[38] R Bahuguna. Fingerprint verification using hologram matched filterings. In Proc. Biometric Cons-ortium Eighth Meeting, San Jose, California, June, 1996
[39] 洪波，荣钢，黄韬．一种基于遗传算法的指纹比对算法．清华大学学报(自然科学版)，2000，41(3)．93～96
[40] A. K.Jain, S.Pankanti, S.Prabhakar, A.Ross. Recent Advances in Fingerprint Verification. The 3rd International Conference on Audio and Video-Based Person Authentication (AVBPA), Sweden, 2001, June. 182～191
[41] B. M. Mehtre, N. N. Murthy, S. Kapoor, B. Chatterjee. Segmentation of fingerprint images using the directional images. Pattern Recognition, 1995, 28. 1657～1672
[42] A. M. Bazen, S. H. Crerez. Directional field computation for fingerprints based on the principal component analysis of local gradients. Proc of ProeRISC2000, 11th Annual Workshop on Circuits, Systems and Signal Processing, Nov, 2000
[43] Lee Chih-Jen, Wang Sheng-De. Fingerprint feature extraction using Gabor filters. Electronics Letters, 1999, 35 (4) .298～290
[44] Andrew W. Senior, Ruud M.Bolle. Improved Fingerprint Matching by Distortion Removal. IEICE Transactions on Information and Systems, 2001, E84-D (7). 825～832
[45] Zhou J., Rong G., Bian ZQ., He D.. Effective algorithm for rolled fingerprint construction. Electronics Letters, 2001, 37 (8) .492～494
[46] Tico M, Saarinen J, Kuosmanen P.. Wavelet domain features for fingerprint recognition. Electronics Letters, 2001, 37 (1). 21～22
[47] Jiang XD., Ser W., Yau WY.. Detecting the fingerprint minutiae by adaptive tracing the gray-level ridge. Partern Recognition, 2001, 34 (5) .999～1013
[48] HE Di, RONG Gang, ZHOU Jie. Image Mosaicing Algorithm for Rolled Fingerprint Construction. Tsinghua Science and Technology, 2002, 7 (3) .317～321
[49] Chang JH., Fan KC.. Fingerprint ridge allocation in direct gray-scale domain. Pattern Recognition, 2001, 34 (10). 1907～1925
[50] Fumihito Arai, Toshio Fukuda. Fingerprint image sensing using micromechanical key and extraction algorithm for sensed fingerprint image. Journal of Robotics and Mechatronies, 2001, 13 (5) .458～463
[51] Chang JH., Fan KC.. A new model for fingerprint classification by ridge distribution sequences. Pattern Recognition, 2002, 35 (6) .1209～1223
[52] Prabhakar S., Jain AK.. Decision-level fusion in fingerprint verification. Pattern Recognition, 2002, 35 (4) .861～874
[53] E. Newham. The Biometric Report. SJB Services. New York, 1995
[54] 王崇文，李见为，郑治伟等．一种基于点模式匹配的指纹识别方法．重庆大学学报(自然科学版)，2002，25(6)．27～31
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