虹膜定位算法研究及其嵌入式软件平台设计
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摘要
虹膜识别技术是一种新兴的生物特征识别技术。相对其他生物特征识别技术(指纹识别,面部识别,声音识别等)而言,虹膜识别技术具有以下几个特点:稳定性、高可靠性和非接触性。这些特点使得虹膜识别具有非常广阔的应用前景。
本文在前人研究的基础上,对虹膜识别的一些核心算法、嵌入式虹膜识别系统都做了一定的研究和改进。本文主要的研究工作包含以下几个方面:
一、在虹膜图像定位算法中,本文研究了二种新的虹膜定位算法。第一种算法是基于灰度信息和分数阶微分边缘检测的,在内边缘定位上由于内边缘定位比较简单因此采用快速的基于灰度信息的方法,在外边缘定位上采用分数阶微分边缘检测的方法。另外一种算法是基于SUSAN边缘检测算子的,主要是侧重于外边缘的定位。由于SUSAN边缘检测算子具有积分特性,不会对虹膜的纹理细节信息造成大幅度的衰减,并且对局部噪声不敏感,因此非常适合在虹膜外边缘定位上的运用,取得了很好的定位效果。
二、在虹膜归一化算法方面,本文研究了一种基于极坐标变换的虹膜归一化算法。该归一化算法采用同心圆的方式进行极坐标转换以方便运算,针对归一化图像对比度比较低的情况进行了光照估计。采用了双三次插值和直方图均衡化的方法对虹膜归一化图像进行了增强。
三、阐述了嵌入式虹膜识别系统的相关硬件,针对项目情况设计了基于TI DSP平台的DSP/BIOS嵌入式系统,在系统中进行了任务设计调度以及任务间的通信和同步,给出了算法在TI TMS320C6713b上的移植和优化方法。
本文研究的虹膜识别核心算法在CASIA虹膜数据库(version 2.0)及实验室虹膜数据库中进行了测试实验,并得出了较好的识别效果。
Iris recognition is an emerging biometrics technology. Compared with the other biometrics technologies (fingerprint recognition, facial recognition voice recognition, etc.), iris recognition has the following characteristics: stability, high reliability, non-contact. Therefore, it will be widely used in the future.
This thesis made research and improvement of the iris recognition kernel algorithms. The main tasks of this thesis include:
First, at the iris image localization stage, two new localization methods are proposed. The first method is based on gray information and fractional differential. In iris inner localization, compare with iris outer localization, iris inner localization is simple, so use the fast method based gray information. In iris outer localization, use fractional differential edge detection. The second method is based on SUSAN edge detector. This method is emphasized on iris outer localization. The SUSAN edge detector has the integral characteristic, so it will not depauperate much iris texture. Also, SUSAN edge detector will not impacted by local noise.
Second, at the normalization stage, we propose a polar coordinate transform resolution. Use concentric circle as the normalization style. Take illumination estimation to change the low contrast of mormalized image. Also, to enhance image, we use bicubic interpolation and histogram equalization.
Third, introduce the hardware of embedded iris recognition system, design DSP/BIOS based on TI DSP. Transplant and optimize the algorithm to TI TMS320 C6713b DSPs platform.
The algorithm experiments are done in the CASIA iris database (version 2.0) and Lab iris database, and good recognition results are achieved.
本文在前人研究的基础上,对虹膜识别的一些核心算法、嵌入式虹膜识别系统都做了一定的研究和改进。本文主要的研究工作包含以下几个方面:
一、在虹膜图像定位算法中,本文研究了二种新的虹膜定位算法。第一种算法是基于灰度信息和分数阶微分边缘检测的,在内边缘定位上由于内边缘定位比较简单因此采用快速的基于灰度信息的方法,在外边缘定位上采用分数阶微分边缘检测的方法。另外一种算法是基于SUSAN边缘检测算子的,主要是侧重于外边缘的定位。由于SUSAN边缘检测算子具有积分特性,不会对虹膜的纹理细节信息造成大幅度的衰减,并且对局部噪声不敏感,因此非常适合在虹膜外边缘定位上的运用,取得了很好的定位效果。
二、在虹膜归一化算法方面,本文研究了一种基于极坐标变换的虹膜归一化算法。该归一化算法采用同心圆的方式进行极坐标转换以方便运算,针对归一化图像对比度比较低的情况进行了光照估计。采用了双三次插值和直方图均衡化的方法对虹膜归一化图像进行了增强。
三、阐述了嵌入式虹膜识别系统的相关硬件,针对项目情况设计了基于TI DSP平台的DSP/BIOS嵌入式系统,在系统中进行了任务设计调度以及任务间的通信和同步,给出了算法在TI TMS320C6713b上的移植和优化方法。
本文研究的虹膜识别核心算法在CASIA虹膜数据库(version 2.0)及实验室虹膜数据库中进行了测试实验,并得出了较好的识别效果。
Iris recognition is an emerging biometrics technology. Compared with the other biometrics technologies (fingerprint recognition, facial recognition voice recognition, etc.), iris recognition has the following characteristics: stability, high reliability, non-contact. Therefore, it will be widely used in the future.
This thesis made research and improvement of the iris recognition kernel algorithms. The main tasks of this thesis include:
First, at the iris image localization stage, two new localization methods are proposed. The first method is based on gray information and fractional differential. In iris inner localization, compare with iris outer localization, iris inner localization is simple, so use the fast method based gray information. In iris outer localization, use fractional differential edge detection. The second method is based on SUSAN edge detector. This method is emphasized on iris outer localization. The SUSAN edge detector has the integral characteristic, so it will not depauperate much iris texture. Also, SUSAN edge detector will not impacted by local noise.
Second, at the normalization stage, we propose a polar coordinate transform resolution. Use concentric circle as the normalization style. Take illumination estimation to change the low contrast of mormalized image. Also, to enhance image, we use bicubic interpolation and histogram equalization.
Third, introduce the hardware of embedded iris recognition system, design DSP/BIOS based on TI DSP. Transplant and optimize the algorithm to TI TMS320 C6713b DSPs platform.
The algorithm experiments are done in the CASIA iris database (version 2.0) and Lab iris database, and good recognition results are achieved.
引文
[1]孙冬梅,裘正定.生物特征识别技术综述.电子学报,2001,29(12A) : 1744-1748
[2] L.Flom, A.Safir,“Iris Recognition System”, U.S. Patent, No.4641394, 1987
[3] J.Daugman,Biometric Personal Identification System Based on Iris Analysis, U.S. patent 5291560,March 1,1994
[4] J.Daugman,“High Confidence Visual Recognition of Persons by a Test of Statistical Independence”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.15, No.11, pp.1148-1161, 1993
[5] J.G.Daugman, How Iris Recognition Works. IEEE Trans on Circuits & Systems for Video Technology, 2004, vol. 14, issue 1, : 21-30
[6] R.Wildes, J.Asmuth, et al.,“A Machine-Vision System for Iris Recognition”, Machine Vision and Applications, Vol.9, pp.1-8, 1996
[7] W. Boles, B. Boashah. A Human Identification Technique Using Images of the Iris and Wavelet Transform. IEEE transactions on Signal Processing, 1998, 46(4): 1185-1188
[8]谭铁牛,朱勇,王蕴红,虹膜图象采集装置,实用新型,国家知识产权局,中国, No.99217063, 2000
[9] J. Daugman, Recognising Persons by Their Iris Patterns, Lecture Notes in Computer Science (2004) : 5-25
[10] Y. Zhu, T. Tan and Y. Wang, Biometric Personal Identification Based on Iris Patterns,International Conference on Pattern Recognition (ICPR'2000), vol. II (2000) : 805-808
[11] L. Ma, Y. Wang and T. Tan, Iris Recognition Based on Multichannel Gabor Filtering, Proc. of the 5th Asian Conference on Computer Vision (ACCV2002), vol. I (2002) : 279-283
[12]邵帅,基于核方法的虹膜识别算法研究:[硕士学位论文],成都:电子科技大学,4-5, 22-23
[13]汪洁,虹膜识别系统中的算法研究与驱动程序设计:[硕士学位论文],成都:电子科技大学,2007:4-5, 17-18
[14]胡正平,王成儒,于莉娜.基于改进随机Hough变换的虹膜定位算法.仪器仪表学报,2003,24(5) : 477-479
[15] L. Ma and T. Tan, Personal Identification Based on Iris Texture Analysis, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 25, no. 12 (2003) : 1519-1533
[16] L. Ma, Y. Wang and T. Tan, Iris Recognition Using Circular Sysmmetric Filters, Proc.of the 6th International Conference on Pattern Recognition, vol. II (2002) : 414-417
[17]王蕴红,朱勇,谭铁牛,基于虹膜识别的身份鉴别,自动化学报, vol. 28, no. 1 (2002) : 1-10
[18]田启川,潘泉,张洪才,程咏梅,Hough变换在虹膜区域分割中的应用,计算机应用研究,第一期,(2005):249-251
[19]罗家辉,冯平,哈力旦.A,MATLAB 7.0在图像处理中的应用。机械工业出版社,2005
[20]潘力立,虹膜识别算法的研究及其实现:[硕士学位论文]。成都:电子科技大学,2007:34-35,37-39
[21]钟志光,卢君,刘伟荣,Visual C++.NET数字图像处理实例与解析。清华大学出版社,2003
[22] http://www.ica1.uni-stuttgart.de/Jahresberichte/00/node50.html
[23]蒲亦非,将分数阶微分演算引入数字图像处理.四川大学学报(工程科学版),vol.39,no.3 (2007):124-132
[24] Introductory Notes on Fractional Calculus. www.xuru.org
[25] YaoKui, SuWeiyi, ZhouSongping, ON THE FRACTIONAL CALCULUS FUNCTIONS OF A FRACTAL FUNCTION. Appl.Math.J.Chinese Univ.Ser.B. 2002: 377-381
[26] Adam Loverro, Fractional Calculus: History, Definitions and Applications for the Engineer. Department of Aerospace and Mechanical Engineering University of Notre Dame, 2004
[27] FRACTIONAL CALCULUS: Integral and Differential Equations of Fractional Order. CISM LECTURE NOTES, International Centre for Mechanical Sciences, Palazzo del Torso, Piazza, Garibaldi, Udine, Italy.
[28] A.Oustaloup, A.Ballouk,B.Bansard, Partial Differential Equations and Non Integer Derivation. Systems Engineering in the Service of Humans’, vol.2, (1993): 166-173
[29]李惠光,王平顺,李国友,采用分数阶导数的高斯滤波微分算子边缘检测方法。冶金自动化增刊,(2004):195-198
[30]薛定宇,陈阳泉,高等应用数学问题的MATLAB求解。清华大学出版社,2004:384-400
[31] B.Mathieu, P.Melchior, A.Oustaloup, Ch.Ceyral, Fractional differential for edge detection. Signal Processing 83 (2003): 2421-2432
[32] J.You, S.Hungnahally, A.Sattar, Fractional Discrimination for Texture Image Segmentation. International Conference on Image Processing, vol.1 (1997): 220-223
[33] S.M.Smith, J.M.Brady, SUSAN-A New Approach to Low Level Image Processing. Technical Report TR95SMS1c, 1995
[34] http://users.fmrib.ox.ac.uk/~steve/susan/
[35] DongxiangZhou, Yun-huiLiu, XuanpingCai, An Efficient and Robust Corner Detection Algorithm. Proceedings of the 5th World Congress on Intelligent Control and Automation, Hangzhou,China, (2004): 4020-4024
[36]陆宏伟,于起峰,最小核值相似区低层次图像处理算法的改进及应用。应用光学,Vol.21, No.1, (2000): 32-37
[37] S.M.Smith, Edge Thinning used in the SUSAN Edge Detecot. Technical Report TR95SMS5, 1995
[38] Marcelo M.Perez, Tim J.Pennis, An Adaptive Implementation of the SUSAN Method for Image Edge and Feature Detection. Proceedings International Conference on Image Processing, (1997): 394-397
[39] Rafael C. Gonzalez, Richard E. Woods.数字图像处理(第二版)(阮秋琦,阮宇智等译)。北京:电子工业出版社,2003, 463-474
[40]王艳莉,插值算法应用在图像缩放中研究,烟台教育学院学报,Vol.11, No.1, 2005
[41] Texas Instruments. Code Composer Studio User’s Guide, 1999
[42] Texas Instruments. TMS320C6713, TMS320C6713b FLOATING-POINT DIGITAL SIGNAL PROCESSORS, 2004
[43] Texas Instruments. TMS320C6000 DSP External Memory Interface (EMIF) Reference Guide, 2004
[44] Texas Instruments. TMS320C6000 DSP Inter-Integrated Circuit (I2C) Module Reference Guide, 2002.
[45]广东周立功单片机发展有限公司。I2C总线规范,2003
[46] Silicon Storage Technology, Inc. 16Mbit/32Mbit/64Mbit (×16) Multi-Purpose Flash Plus, 2003
[47] Hynix Semiconductor, Inc. HY57V561620C(L)T(P) 4Banks×4M×16Bit Synchronous DRAM, 2004
[48]广州周立功单片机发展有限公司。ZLG7290 I2C接口键盘及LED驱动器
[49]彭启琮,管庆,DSP集成开发环境-CCS及DSP/BIOS的原理及应用。电子工业出版社,2005
[50] Texas Instruments. TMS320C6000 DSP/BIOS User’s Guide. 2000
[51] Texas Instruments. TMS320C6000 Chip Support Library API Reference Guide. 2004
[52]李方慧,王飞,何佩琨。TMS320C6000系列DSPs原理与应用(第二版)。北京:电子工业出版社,2003
[53] http://www.woodpecker.org.cn/
[54] Texas Instruments. Optimizing C Compiler Tutorial, 2003
[55] Texas Instruments.Programmer’s Guide, 2002
[56] Texas Instruments.TMS320C6000 C Compiler C Implementation of Intrinsics, 2002
[57] Texas Instruments.TMS320C6000 C Debug, 2003
[58] Texas Instruments.TMS320C6000 optimazing Compiler. 2004
[59] Texas Instruments. TMS320C6000 DSP Cache User’s Guide, 2003
[2] L.Flom, A.Safir,“Iris Recognition System”, U.S. Patent, No.4641394, 1987
[3] J.Daugman,Biometric Personal Identification System Based on Iris Analysis, U.S. patent 5291560,March 1,1994
[4] J.Daugman,“High Confidence Visual Recognition of Persons by a Test of Statistical Independence”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.15, No.11, pp.1148-1161, 1993
[5] J.G.Daugman, How Iris Recognition Works. IEEE Trans on Circuits & Systems for Video Technology, 2004, vol. 14, issue 1, : 21-30
[6] R.Wildes, J.Asmuth, et al.,“A Machine-Vision System for Iris Recognition”, Machine Vision and Applications, Vol.9, pp.1-8, 1996
[7] W. Boles, B. Boashah. A Human Identification Technique Using Images of the Iris and Wavelet Transform. IEEE transactions on Signal Processing, 1998, 46(4): 1185-1188
[8]谭铁牛,朱勇,王蕴红,虹膜图象采集装置,实用新型,国家知识产权局,中国, No.99217063, 2000
[9] J. Daugman, Recognising Persons by Their Iris Patterns, Lecture Notes in Computer Science (2004) : 5-25
[10] Y. Zhu, T. Tan and Y. Wang, Biometric Personal Identification Based on Iris Patterns,International Conference on Pattern Recognition (ICPR'2000), vol. II (2000) : 805-808
[11] L. Ma, Y. Wang and T. Tan, Iris Recognition Based on Multichannel Gabor Filtering, Proc. of the 5th Asian Conference on Computer Vision (ACCV2002), vol. I (2002) : 279-283
[12]邵帅,基于核方法的虹膜识别算法研究:[硕士学位论文],成都:电子科技大学,4-5, 22-23
[13]汪洁,虹膜识别系统中的算法研究与驱动程序设计:[硕士学位论文],成都:电子科技大学,2007:4-5, 17-18
[14]胡正平,王成儒,于莉娜.基于改进随机Hough变换的虹膜定位算法.仪器仪表学报,2003,24(5) : 477-479
[15] L. Ma and T. Tan, Personal Identification Based on Iris Texture Analysis, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 25, no. 12 (2003) : 1519-1533
[16] L. Ma, Y. Wang and T. Tan, Iris Recognition Using Circular Sysmmetric Filters, Proc.of the 6th International Conference on Pattern Recognition, vol. II (2002) : 414-417
[17]王蕴红,朱勇,谭铁牛,基于虹膜识别的身份鉴别,自动化学报, vol. 28, no. 1 (2002) : 1-10
[18]田启川,潘泉,张洪才,程咏梅,Hough变换在虹膜区域分割中的应用,计算机应用研究,第一期,(2005):249-251
[19]罗家辉,冯平,哈力旦.A,MATLAB 7.0在图像处理中的应用。机械工业出版社,2005
[20]潘力立,虹膜识别算法的研究及其实现:[硕士学位论文]。成都:电子科技大学,2007:34-35,37-39
[21]钟志光,卢君,刘伟荣,Visual C++.NET数字图像处理实例与解析。清华大学出版社,2003
[22] http://www.ica1.uni-stuttgart.de/Jahresberichte/00/node50.html
[23]蒲亦非,将分数阶微分演算引入数字图像处理.四川大学学报(工程科学版),vol.39,no.3 (2007):124-132
[24] Introductory Notes on Fractional Calculus. www.xuru.org
[25] YaoKui, SuWeiyi, ZhouSongping, ON THE FRACTIONAL CALCULUS FUNCTIONS OF A FRACTAL FUNCTION. Appl.Math.J.Chinese Univ.Ser.B. 2002: 377-381
[26] Adam Loverro, Fractional Calculus: History, Definitions and Applications for the Engineer. Department of Aerospace and Mechanical Engineering University of Notre Dame, 2004
[27] FRACTIONAL CALCULUS: Integral and Differential Equations of Fractional Order. CISM LECTURE NOTES, International Centre for Mechanical Sciences, Palazzo del Torso, Piazza, Garibaldi, Udine, Italy.
[28] A.Oustaloup, A.Ballouk,B.Bansard, Partial Differential Equations and Non Integer Derivation. Systems Engineering in the Service of Humans’, vol.2, (1993): 166-173
[29]李惠光,王平顺,李国友,采用分数阶导数的高斯滤波微分算子边缘检测方法。冶金自动化增刊,(2004):195-198
[30]薛定宇,陈阳泉,高等应用数学问题的MATLAB求解。清华大学出版社,2004:384-400
[31] B.Mathieu, P.Melchior, A.Oustaloup, Ch.Ceyral, Fractional differential for edge detection. Signal Processing 83 (2003): 2421-2432
[32] J.You, S.Hungnahally, A.Sattar, Fractional Discrimination for Texture Image Segmentation. International Conference on Image Processing, vol.1 (1997): 220-223
[33] S.M.Smith, J.M.Brady, SUSAN-A New Approach to Low Level Image Processing. Technical Report TR95SMS1c, 1995
[34] http://users.fmrib.ox.ac.uk/~steve/susan/
[35] DongxiangZhou, Yun-huiLiu, XuanpingCai, An Efficient and Robust Corner Detection Algorithm. Proceedings of the 5th World Congress on Intelligent Control and Automation, Hangzhou,China, (2004): 4020-4024
[36]陆宏伟,于起峰,最小核值相似区低层次图像处理算法的改进及应用。应用光学,Vol.21, No.1, (2000): 32-37
[37] S.M.Smith, Edge Thinning used in the SUSAN Edge Detecot. Technical Report TR95SMS5, 1995
[38] Marcelo M.Perez, Tim J.Pennis, An Adaptive Implementation of the SUSAN Method for Image Edge and Feature Detection. Proceedings International Conference on Image Processing, (1997): 394-397
[39] Rafael C. Gonzalez, Richard E. Woods.数字图像处理(第二版)(阮秋琦,阮宇智等译)。北京:电子工业出版社,2003, 463-474
[40]王艳莉,插值算法应用在图像缩放中研究,烟台教育学院学报,Vol.11, No.1, 2005
[41] Texas Instruments. Code Composer Studio User’s Guide, 1999
[42] Texas Instruments. TMS320C6713, TMS320C6713b FLOATING-POINT DIGITAL SIGNAL PROCESSORS, 2004
[43] Texas Instruments. TMS320C6000 DSP External Memory Interface (EMIF) Reference Guide, 2004
[44] Texas Instruments. TMS320C6000 DSP Inter-Integrated Circuit (I2C) Module Reference Guide, 2002.
[45]广东周立功单片机发展有限公司。I2C总线规范,2003
[46] Silicon Storage Technology, Inc. 16Mbit/32Mbit/64Mbit (×16) Multi-Purpose Flash Plus, 2003
[47] Hynix Semiconductor, Inc. HY57V561620C(L)T(P) 4Banks×4M×16Bit Synchronous DRAM, 2004
[48]广州周立功单片机发展有限公司。ZLG7290 I2C接口键盘及LED驱动器
[49]彭启琮,管庆,DSP集成开发环境-CCS及DSP/BIOS的原理及应用。电子工业出版社,2005
[50] Texas Instruments. TMS320C6000 DSP/BIOS User’s Guide. 2000
[51] Texas Instruments. TMS320C6000 Chip Support Library API Reference Guide. 2004
[52]李方慧,王飞,何佩琨。TMS320C6000系列DSPs原理与应用(第二版)。北京:电子工业出版社,2003
[53] http://www.woodpecker.org.cn/
[54] Texas Instruments. Optimizing C Compiler Tutorial, 2003
[55] Texas Instruments.Programmer’s Guide, 2002
[56] Texas Instruments.TMS320C6000 C Compiler C Implementation of Intrinsics, 2002
[57] Texas Instruments.TMS320C6000 C Debug, 2003
[58] Texas Instruments.TMS320C6000 optimazing Compiler. 2004
[59] Texas Instruments. TMS320C6000 DSP Cache User’s Guide, 2003