掌纹掌脉信息融合算法设计
摘要
掌纹和掌脉识别技术是最近几年才发展起来的新的生物特征识别技术,以其独特的优势得到了国内外生物特征识别领域研究人员的广泛关注。本文在国家“863”相关课题的支持下,围绕掌纹和掌脉图像信息融合,开展了下述的研究工作:
1)利用掌脉和掌纹的成像原理,本文提出了利用JAI公司的AD080CL多光谱摄像机采集掌纹和掌脉图像。由于是利用单个摄像机采集所以可以不必进行掌纹和掌脉图像的配准。
2)提出了对掌纹和掌脉图像的预处理流程,因为在采集红外图像的时候必然引入噪声。预处理中采用小波模极大值方法实现在图像去噪和增强,同时也对感兴趣区域的选取做了一定的研究。
3)利用双树复数小波和对抗融合技术实现掌纹和掌脉图像的融合,同时对融合规则做了重点介绍。随后也介绍了离散小波变换和平移不变小波变换的融合技术,主要用于和前述两个算法做对比。
4)采用熵、互信息量和算法耗时对几个融合方法做了初步的评价,证明了双树复数小波和对抗融合方法的优越性。最后利用排序测度方法对单一的掌纹、单一的掌脉、双树复数小波和对抗融合方法做特征提取,继而进行特征匹配,识别效果表明采用信息融合的方法在性能上明显优于单一特征的方法。
Palmprint and palm vein recognition technologies developed in recent years are new biometric technologies. With their unique advantages, palm vein and palmprint recognition attract widespread attention of the domestic and international researchers in the field of biometric. Supported by the related‘863’projects of the state, this thesis focuses on the fusion of palmprint image and palm vein image. Our contributions include:
1) Considering the imaging principle of palmprint and palm vein, we propose to use AD080CL multispectral camera of JAL to get palmprint and palm vein image. Because these images are from the same camera, registrations of images are not needed.
2) Preprocessing of palmprint and palm vein image is proposed, the reason is that infrared imaging system inevitably have palm vein image with noise. In the process of preprocessing wavelet modulus maximum algorithm are used for image denoising and image enhancement,and we also do some research on how to get ROI of palmprint and palm vein image.
3) Dual tree complex wavelet tansform (DTCWT) and opponent processing are proposed for the fusion of palmprint and palm vein image, and fusion rules are emphasized. Also discrete wavelet transform (DWT) and shift invariant discrete wavelet transform (SIDWT) are introduced which are used to compare with the formal two methods.
4) Entropy, mutual information and elapsed time are calculated, the experimental results show that DTCWT and opponent processing have more advantages than others. Finally ordinal mesure are used for feature extraction in single palmprint, single palm vein, DTCWT and opponent processing system, and by the result of feature matching we can conclude that information fusion methods have excellent performance than single one.
1)利用掌脉和掌纹的成像原理,本文提出了利用JAI公司的AD080CL多光谱摄像机采集掌纹和掌脉图像。由于是利用单个摄像机采集所以可以不必进行掌纹和掌脉图像的配准。
2)提出了对掌纹和掌脉图像的预处理流程,因为在采集红外图像的时候必然引入噪声。预处理中采用小波模极大值方法实现在图像去噪和增强,同时也对感兴趣区域的选取做了一定的研究。
3)利用双树复数小波和对抗融合技术实现掌纹和掌脉图像的融合,同时对融合规则做了重点介绍。随后也介绍了离散小波变换和平移不变小波变换的融合技术,主要用于和前述两个算法做对比。
4)采用熵、互信息量和算法耗时对几个融合方法做了初步的评价,证明了双树复数小波和对抗融合方法的优越性。最后利用排序测度方法对单一的掌纹、单一的掌脉、双树复数小波和对抗融合方法做特征提取,继而进行特征匹配,识别效果表明采用信息融合的方法在性能上明显优于单一特征的方法。
Palmprint and palm vein recognition technologies developed in recent years are new biometric technologies. With their unique advantages, palm vein and palmprint recognition attract widespread attention of the domestic and international researchers in the field of biometric. Supported by the related‘863’projects of the state, this thesis focuses on the fusion of palmprint image and palm vein image. Our contributions include:
1) Considering the imaging principle of palmprint and palm vein, we propose to use AD080CL multispectral camera of JAL to get palmprint and palm vein image. Because these images are from the same camera, registrations of images are not needed.
2) Preprocessing of palmprint and palm vein image is proposed, the reason is that infrared imaging system inevitably have palm vein image with noise. In the process of preprocessing wavelet modulus maximum algorithm are used for image denoising and image enhancement,and we also do some research on how to get ROI of palmprint and palm vein image.
3) Dual tree complex wavelet tansform (DTCWT) and opponent processing are proposed for the fusion of palmprint and palm vein image, and fusion rules are emphasized. Also discrete wavelet transform (DWT) and shift invariant discrete wavelet transform (SIDWT) are introduced which are used to compare with the formal two methods.
4) Entropy, mutual information and elapsed time are calculated, the experimental results show that DTCWT and opponent processing have more advantages than others. Finally ordinal mesure are used for feature extraction in single palmprint, single palm vein, DTCWT and opponent processing system, and by the result of feature matching we can conclude that information fusion methods have excellent performance than single one.
引文
[1] D. Zhang. Automated Biometrics-Technologies and Systems. Kluwer Academic Publishers, 2000.
[2]田捷,杨鑫编著.生物特征识别技术理论与应用.北京:电子工业出版社,2005.
[3] J. L. Dugelay, J.C.Junqua, C.R.Kotropoulos. Ren- cent advances in biometric person authentication. IEEE International Conference on Acoustics, Speech, and Signal Processing. 4(4):4060-4063, 2002.
[4] V. Matyas, Z.Riha. Toward Reliable User Authentication through Biometrics. IEEE Security & Privacy. 1(3):45-49, 2003.
[5] S. Prabhakar, S. Pankanti, A. K. Jain. Biometric Recognition: Security and Privacy Concerns. IEEE Security & Privacy. 1(2):33-42, 2003.
[6] A. Jain, A. Ross, S. Prabhakar. An Introduction to Biometric Recognition, IEEE Trans. on Circuit and System for Video Technology. 14(1): 4-20, 2004.
[7] Biometrics Market Report 2009~2014. International Biometric Group.2009, Available: http://www.biometricgroup.com/reports/public/market_report.php.S.Pankanti, S.Prabhakar, A.K.Jain. On the individuality of fingerprints. Kauai, HI: Institute of Electrical and Electronics Engineers Computer Society. 2001.
[8] D. Zhang. Palmprint Authentication [M]. Kluwer Academic Publishers, Boston, 2004.
[9] A. Kong, D. Zhang, M. Kamel. A survey of palmprint recognition [J]. Pattern Recognition, 2009, 42, 1408~1418.
[10] M. Wong, D. Zhang, W. Kong, G. Lu. Real-time palmprint acquisition system design [J]. IEEE Proceeding on Vision and Image Signal Processing, 2005, 152(5): 527~534.
[11] D. Zhang, W. Kong, J. You, M. Wong. Online palmprint identification [J]. IEEE Transactions on. Pattern Analysis and. Machine Intelligence, 2003, 25(9): 1041~1050.
[12] D. Zhang, Z. Guo, G. Lu, L. Zhang, W. Zuo. An Online System of Multispectral Palmprint Verification [J]. IEEE Transaction on Instrumentation and Measurement, 2010, 59 (2): 480~490.
[13] W. Li, D. Zhang, Z. Xu. Image alignment based on invariant features for palmprint identification [J]. Signal Processing: Image Communication, 2003, 373~379.
[14] D. Zhang, W. Shu. Two novel characteristics in palmprint verification: datum point invariance and line feature matching [J]. Pattern Recognition, 1999, 691~702.
[15] J. You, W. Li, D. Zhang. Hierarchical palmprint identification via multiple feature extraction [J]. Pattern Recognition, 2002, 35(4): 847~859.
[16] G. Lu, D. Zhang, K. Wang. Palmprint Recognition Using Eigenpalms Features [J]. Pattern Recognition Letters, 2003, 24:1463~1467.
[17] X. Wu, D. Zhang, K. Wang. Fisherpalms based palmprint recognition [J]. Pattern Recognition Letters, 2003, 24: 2829~2838.
[18] W. Li, D. Zhang, Z. Xu. Palmprint Identification by Fourier Transform [J]. International Journal of Pattern Recognition and Artificial Intelligence, 2002, 16(4): 417~432.
[19] J. You, W. Kong, D. Zhang, K. Cheung. On Hierarchical Palmprint Coding with Multi-features for Personal Identification in Large Databases [J]. IEEE Transactions on Circuit Systems for Video Technology, 2004, 14(.2): 234~243.
[20] L. Zhang, D. Zhang. Characterization of Palmprints by Wavelet Signatures via Directional Context Modeling [J]. IEEE Transactions on SMC-B, 2003, 34(3): 1335~1347.
[21] W. Shu, G. Rong, Z. Bian, D. Zhang. Automatic Palmprint Verification [J]. Intrenational Journal of Image and Graphics, 2001, 1:135~151.
[22] W. Kong, D. Zhang, W. Li. Palmprint feature extraction using 2-D Gabor Filters, Pattern Recognition 2003, 36: 2339~2347.
[23] D. Zhang, G. Lu, A. Kong, M. Wong. Online Palmprint Identification System for Civil Application [J]. Journal of Computer Science and Technology, 2005, 20(1): 1~8.
[24] D. Zhang, G. Lu, W. Kong, M. Wong. Palmprint Authentication Technologies, Systems and Applications [C]. The 5th Chinese Conference on Biometrics Recognition. Lecture Notes in Computer Science, Springer-Verlag Heidelberg. 2004: 78~89.
[25] D. Zhang, G. Lu, W. Kong, M. Wong. Palmprint Authentication System for Civil Applications [C]. ECCV 2004 International Workshop, Lecture Notes in Computer Science, Springer-Verlag Heidelberg. 2004: 217~228.
[26] N. Duta, A. Jain, K. Mardia. Matching of Palmprint [J]. Pattern Recognition Letters, 2001. 23(4): 477~485.
[27] A. Jain, J. Feng. Latent Palmprint Matching [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2009, 31(6):1032~1047.
[28] A. Kumar, D. Wong, H. Shen, A. Jain. Personal Verification using Palmprint and Hand Geometry Biometric [C]. Lecture Notes in Computer Science, 2003, 2688: 668~678
[29] C. Tee, A. Jin, M. Ong, D. Ling. An automated palmprint recognition system [J]. Image and Vision Computing, 2005, 23(5): .501~515.
[30] C. Tee, T. Andrew, G. Michael, N. David. PalmHashing: A Novel Approach for Dual Factor Authentication [J]. Pattern Analysis and Applications. Springer-Verlag, 2003.
[31] C. Tee, T. Andrew, G. Michael, N. David. Palmprint Recognition with PCA and ICA [C]. Conference of Image and Vision Computing New Zealand 2003 (IVCNZ’03), 2003:227~232.
[32] C. Han, H. Cheng, C. Lin, K. Fan. Personal authentication using palmprint features [J]. Pattern Recognition, 2003, 36(2): 371~381.
[33] C. Han. A hand-based personal authentication using a coarse-to-fine strategy [J]. Image and Vision Computing, 2004, 22: 909–918.
[34] C. Lin, T. Chuang, K. Fan. Palmprint verification using hierarchical decomposition [J]. Pattern Recognition, 38(10): 2639~2652.
[35]左铁东,张环,胡德文.手掌静脉识别系统的研究与设计.计算机测量与控制,2009
[36] R. B. Cai, D. W. Hu, Image fusion of palmprint and palm vein, Proceedings of IEEE International Congress on Image and Signal Processing, Vol. 6, 2010, pp. 2778-2780.
[37] K. Shimizu. Optical trans-body imaging:feasibility of CT and functional imaging of living body [J]. Japanese Journal of Medicine Philosophic, 1992, 11: 620~629.
[38] M.Kouno, H.Ueki, S.Umemura A new method for the identification of individuals by using of vein pattern matching of a finger, Proceedings of the Fifth Symposium on Pattern Measurement, (Yamaguchi, Japan), 9-12, 2000.
[39] N.Miura, A.Nagasaka. Takafumi Miyatake Feature extraction o finger vein patterns based on iterative line tracking and its application to personal identification, Systems and Computers in Japan 35(7): 61-71, 2004.
[40] W.Shen, M.Surette, R.Khanna. Evaluation of automated biometrics-based identify- ication and verification systems. In: Special issue on automated biometric systems. Proc IEEE 85(9):1463–1478, 1997.
[41] C.L.Lin, K.C. Fan. Biometric verification using thermal images of palm-dorsa vein patterns. IEEE Trans Circuits Sys Video Tech, 14(2): 199-213, Feb. 2004.
[42]林喜荣等.人体手背静脉血管图像的特征提取及匹配.清华大学学报:自然科学版,43(2).164-167, 2003.
[43] W. Masaki, E. Toshio, S. Morito, S. Shigeru. Palm vein authentication technology and its applications [C]. Proceedings of The Biometric Consortium Conference, Hyatt Regency Crystal City, USA, 2005.
[44] http://palmsecure.fujitsu.com/pss/index.php
[45] S.K.Im. A Biometric Identification System by Extracting Hand Vein Patterns. Journal of the Korean Physical Society, 38(3): p. 268-272, 2003.
[46] T.Tanaka, N.Kubo. Biometric authentication by hand vein patterns. In SICE2004 Annual Conference. 2004.
[47]王科俊,丁宇航,王大振.基于静脉识别的身份认证方法研究.科技导报.23(1):p. 35-37, 2005.
[48] K. W. Bowyer, C. Kyong, Patrick Flynn. An Evaluation of Multimodal 2D+3D Face Biometrics [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2005, 27 (4): 619~624.
[49] A. Kumar, D. Zhang. Personal recognition using hand shape and texture [J]. IEEE Transactions on Image Processing, 2006, 15 (8): 2454~2461.
[50] R. Snelick, U. Uludag, A. Mink, M. Indovina, A. Jain. Large Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27 (3): 450~455.
[51] Z. N. Sun, T.N. Tan, Y.H. Wang, S. Z. Li, Ordinal Palmprint Representation for Personal Identification, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, Vol.1, 2005, pp. 279-284
[52] N. Kingsbury. The dual-tree complex wavelet transform: A new technique for shift invariance and directional filters. In: 8th IEEE DSP Workshop; 1998
[53] N. Kingsbury. Complex wavelet transform for shift invariant analysis and filtering of signals. Appl Comput Harmonic Anal 2001; 10(3): 234-253
[54] N. Kingsbury. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. In: IEEE Int. Conf. Image Processing; 2000.
[55]李武,李朝义.视觉感受野外整合野研究的进展[J].神经科学, 1994, 1(2): 1~6.
[56] T. Shou, W. Wang, H. Yu. Orientation biased extended surround of the receptive field of cat retinal ganglion cells [J]. Neuroscience, 2000, 98: 207~212.
[57] E.A. Newman and P.H. Hartline, Integration of Visual and Infrared Information in Bimodal Neurons of the Rattlesnake Optic Tectum, Science 213 (4508), 1981, pp. 789–791.
[58] E.A. Newman and P.H. Hartline, The Infrared‘Vision’of Snakes, Sci. Am. 246 (Mar.), 1982, pp. 116–127.
[59] Waxman et al. Solid-State Color Night Vision: Fusion of Low-Light Visible and Thermal Infrared Imagery [J]. Lincoln laboratory Journal, 1998, 11 (1): 41~60.
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[62] Z. N. Sun, T.N. Tan, Y.H. Wang, Robust Encoding of Local Ordinal Measures: A General Framework of Iris Recognition, Proceeding of International Workshop onBiometric Authentication, Lecture Notes in Computer Science (BioAW), Vol.3087, 2004, pp. 270-282
[63] S. C. Liao, Z. Lei, X. X. Zhu, Z. N. Sun, Z. Stan, and T. N. Tan, Face Recognition Using Ordinal Features, Proceedings of International Conference on Biometrics, Lecture Notes in Computer Sciences, Vol. 3882, 2005, pp. 40-46
[2]田捷,杨鑫编著.生物特征识别技术理论与应用.北京:电子工业出版社,2005.
[3] J. L. Dugelay, J.C.Junqua, C.R.Kotropoulos. Ren- cent advances in biometric person authentication. IEEE International Conference on Acoustics, Speech, and Signal Processing. 4(4):4060-4063, 2002.
[4] V. Matyas, Z.Riha. Toward Reliable User Authentication through Biometrics. IEEE Security & Privacy. 1(3):45-49, 2003.
[5] S. Prabhakar, S. Pankanti, A. K. Jain. Biometric Recognition: Security and Privacy Concerns. IEEE Security & Privacy. 1(2):33-42, 2003.
[6] A. Jain, A. Ross, S. Prabhakar. An Introduction to Biometric Recognition, IEEE Trans. on Circuit and System for Video Technology. 14(1): 4-20, 2004.
[7] Biometrics Market Report 2009~2014. International Biometric Group.2009, Available: http://www.biometricgroup.com/reports/public/market_report.php.S.Pankanti, S.Prabhakar, A.K.Jain. On the individuality of fingerprints. Kauai, HI: Institute of Electrical and Electronics Engineers Computer Society. 2001.
[8] D. Zhang. Palmprint Authentication [M]. Kluwer Academic Publishers, Boston, 2004.
[9] A. Kong, D. Zhang, M. Kamel. A survey of palmprint recognition [J]. Pattern Recognition, 2009, 42, 1408~1418.
[10] M. Wong, D. Zhang, W. Kong, G. Lu. Real-time palmprint acquisition system design [J]. IEEE Proceeding on Vision and Image Signal Processing, 2005, 152(5): 527~534.
[11] D. Zhang, W. Kong, J. You, M. Wong. Online palmprint identification [J]. IEEE Transactions on. Pattern Analysis and. Machine Intelligence, 2003, 25(9): 1041~1050.
[12] D. Zhang, Z. Guo, G. Lu, L. Zhang, W. Zuo. An Online System of Multispectral Palmprint Verification [J]. IEEE Transaction on Instrumentation and Measurement, 2010, 59 (2): 480~490.
[13] W. Li, D. Zhang, Z. Xu. Image alignment based on invariant features for palmprint identification [J]. Signal Processing: Image Communication, 2003, 373~379.
[14] D. Zhang, W. Shu. Two novel characteristics in palmprint verification: datum point invariance and line feature matching [J]. Pattern Recognition, 1999, 691~702.
[15] J. You, W. Li, D. Zhang. Hierarchical palmprint identification via multiple feature extraction [J]. Pattern Recognition, 2002, 35(4): 847~859.
[16] G. Lu, D. Zhang, K. Wang. Palmprint Recognition Using Eigenpalms Features [J]. Pattern Recognition Letters, 2003, 24:1463~1467.
[17] X. Wu, D. Zhang, K. Wang. Fisherpalms based palmprint recognition [J]. Pattern Recognition Letters, 2003, 24: 2829~2838.
[18] W. Li, D. Zhang, Z. Xu. Palmprint Identification by Fourier Transform [J]. International Journal of Pattern Recognition and Artificial Intelligence, 2002, 16(4): 417~432.
[19] J. You, W. Kong, D. Zhang, K. Cheung. On Hierarchical Palmprint Coding with Multi-features for Personal Identification in Large Databases [J]. IEEE Transactions on Circuit Systems for Video Technology, 2004, 14(.2): 234~243.
[20] L. Zhang, D. Zhang. Characterization of Palmprints by Wavelet Signatures via Directional Context Modeling [J]. IEEE Transactions on SMC-B, 2003, 34(3): 1335~1347.
[21] W. Shu, G. Rong, Z. Bian, D. Zhang. Automatic Palmprint Verification [J]. Intrenational Journal of Image and Graphics, 2001, 1:135~151.
[22] W. Kong, D. Zhang, W. Li. Palmprint feature extraction using 2-D Gabor Filters, Pattern Recognition 2003, 36: 2339~2347.
[23] D. Zhang, G. Lu, A. Kong, M. Wong. Online Palmprint Identification System for Civil Application [J]. Journal of Computer Science and Technology, 2005, 20(1): 1~8.
[24] D. Zhang, G. Lu, W. Kong, M. Wong. Palmprint Authentication Technologies, Systems and Applications [C]. The 5th Chinese Conference on Biometrics Recognition. Lecture Notes in Computer Science, Springer-Verlag Heidelberg. 2004: 78~89.
[25] D. Zhang, G. Lu, W. Kong, M. Wong. Palmprint Authentication System for Civil Applications [C]. ECCV 2004 International Workshop, Lecture Notes in Computer Science, Springer-Verlag Heidelberg. 2004: 217~228.
[26] N. Duta, A. Jain, K. Mardia. Matching of Palmprint [J]. Pattern Recognition Letters, 2001. 23(4): 477~485.
[27] A. Jain, J. Feng. Latent Palmprint Matching [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2009, 31(6):1032~1047.
[28] A. Kumar, D. Wong, H. Shen, A. Jain. Personal Verification using Palmprint and Hand Geometry Biometric [C]. Lecture Notes in Computer Science, 2003, 2688: 668~678
[29] C. Tee, A. Jin, M. Ong, D. Ling. An automated palmprint recognition system [J]. Image and Vision Computing, 2005, 23(5): .501~515.
[30] C. Tee, T. Andrew, G. Michael, N. David. PalmHashing: A Novel Approach for Dual Factor Authentication [J]. Pattern Analysis and Applications. Springer-Verlag, 2003.
[31] C. Tee, T. Andrew, G. Michael, N. David. Palmprint Recognition with PCA and ICA [C]. Conference of Image and Vision Computing New Zealand 2003 (IVCNZ’03), 2003:227~232.
[32] C. Han, H. Cheng, C. Lin, K. Fan. Personal authentication using palmprint features [J]. Pattern Recognition, 2003, 36(2): 371~381.
[33] C. Han. A hand-based personal authentication using a coarse-to-fine strategy [J]. Image and Vision Computing, 2004, 22: 909–918.
[34] C. Lin, T. Chuang, K. Fan. Palmprint verification using hierarchical decomposition [J]. Pattern Recognition, 38(10): 2639~2652.
[35]左铁东,张环,胡德文.手掌静脉识别系统的研究与设计.计算机测量与控制,2009
[36] R. B. Cai, D. W. Hu, Image fusion of palmprint and palm vein, Proceedings of IEEE International Congress on Image and Signal Processing, Vol. 6, 2010, pp. 2778-2780.
[37] K. Shimizu. Optical trans-body imaging:feasibility of CT and functional imaging of living body [J]. Japanese Journal of Medicine Philosophic, 1992, 11: 620~629.
[38] M.Kouno, H.Ueki, S.Umemura A new method for the identification of individuals by using of vein pattern matching of a finger, Proceedings of the Fifth Symposium on Pattern Measurement, (Yamaguchi, Japan), 9-12, 2000.
[39] N.Miura, A.Nagasaka. Takafumi Miyatake Feature extraction o finger vein patterns based on iterative line tracking and its application to personal identification, Systems and Computers in Japan 35(7): 61-71, 2004.
[40] W.Shen, M.Surette, R.Khanna. Evaluation of automated biometrics-based identify- ication and verification systems. In: Special issue on automated biometric systems. Proc IEEE 85(9):1463–1478, 1997.
[41] C.L.Lin, K.C. Fan. Biometric verification using thermal images of palm-dorsa vein patterns. IEEE Trans Circuits Sys Video Tech, 14(2): 199-213, Feb. 2004.
[42]林喜荣等.人体手背静脉血管图像的特征提取及匹配.清华大学学报:自然科学版,43(2).164-167, 2003.
[43] W. Masaki, E. Toshio, S. Morito, S. Shigeru. Palm vein authentication technology and its applications [C]. Proceedings of The Biometric Consortium Conference, Hyatt Regency Crystal City, USA, 2005.
[44] http://palmsecure.fujitsu.com/pss/index.php
[45] S.K.Im. A Biometric Identification System by Extracting Hand Vein Patterns. Journal of the Korean Physical Society, 38(3): p. 268-272, 2003.
[46] T.Tanaka, N.Kubo. Biometric authentication by hand vein patterns. In SICE2004 Annual Conference. 2004.
[47]王科俊,丁宇航,王大振.基于静脉识别的身份认证方法研究.科技导报.23(1):p. 35-37, 2005.
[48] K. W. Bowyer, C. Kyong, Patrick Flynn. An Evaluation of Multimodal 2D+3D Face Biometrics [J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2005, 27 (4): 619~624.
[49] A. Kumar, D. Zhang. Personal recognition using hand shape and texture [J]. IEEE Transactions on Image Processing, 2006, 15 (8): 2454~2461.
[50] R. Snelick, U. Uludag, A. Mink, M. Indovina, A. Jain. Large Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27 (3): 450~455.
[51] Z. N. Sun, T.N. Tan, Y.H. Wang, S. Z. Li, Ordinal Palmprint Representation for Personal Identification, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, Vol.1, 2005, pp. 279-284
[52] N. Kingsbury. The dual-tree complex wavelet transform: A new technique for shift invariance and directional filters. In: 8th IEEE DSP Workshop; 1998
[53] N. Kingsbury. Complex wavelet transform for shift invariant analysis and filtering of signals. Appl Comput Harmonic Anal 2001; 10(3): 234-253
[54] N. Kingsbury. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. In: IEEE Int. Conf. Image Processing; 2000.
[55]李武,李朝义.视觉感受野外整合野研究的进展[J].神经科学, 1994, 1(2): 1~6.
[56] T. Shou, W. Wang, H. Yu. Orientation biased extended surround of the receptive field of cat retinal ganglion cells [J]. Neuroscience, 2000, 98: 207~212.
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