掌纹图像压缩加密及其安全认证研究
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摘要
随着信息技术和网络技术的高速发展,信息安全显示出前所未有的重要性。生物识别技术以其特有的稳定性、唯一性和方便性,得到越来越广泛的应用。掌纹识别作为一项新兴的生物识别技术,因具有采样简单、图像信息丰富、用户接受程度高、不易伪造、受噪声干扰小等特点受到国内外研究人员的广泛关注。和其它生物特征识别系统一样,掌纹认证系统也存在健康隐私保护和安全隐患,而这一问题很少得到国内外研究者的关注。
     本论文围绕基于掌纹图像的安全认证技术展开研究,同时讨论了图像有损压缩对掌纹识别认证性能的影响,为掌纹图像的有损和无损压缩编码技术提供了参考。在分析总结前人工作的基础上,主要创新工作如下:
     1、给出安全掌纹认证系统的评价指标,分析了混沌密码在掌纹图像及其模版保护上的应用可行性。基于非线性动力学滤波器具有高的测度熵和高度并行结构的特点,设计了一种易于硬件实现的高效混沌流密码。熵编码位于图像编码的最后阶段,根据图像无损压缩的算法,利用非线性动力学滤波器这一安全混沌模型,设计了安全哥伦布和算术熵编码。基于前馈-反馈非线性动力学滤波器流密码发生器,设计一种安全的随机哥伦布编码,该算法具有较高的编解码效率和大的密钥空间。非线性动力学滤波器的参数设计灵活,据此设计一种安全的随机算术编码。相对于一般流密码,该算法很容易产生雪崩效应,因而具有较高的安全性。
     2、研究掌纹图像无损压缩及其安全编解码。通过分析和测试现有常用的无损图像压缩算法,包括基于变换(整数DCT实现的JPEG、JPEG2000和SP变换)、基于预测的无损压缩算法(LJPEG, CALIC和JPEG-LS)和基于字典压缩的方法(png和UHA),综合考虑,得到JPEG-LS在压缩效率和速度上是目前适合掌纹图像无损压缩算法的结论。根据JPEG-LS编码的特点,利用FFNDF产生混沌流密码,设计了一种复杂度低、对压缩性能没有影响的安全编解码算法。实验结果表明,该算法具有较高的加密效率和安全性。
     3、研究掌纹图像有损压缩对掌纹认证性能的影响。CompCode是目前最优的掌纹认证算法之一。研究了不同图像有损压缩编码对掌纹CompCode认证性能的影响,包括不同变换(基于分块DCT的JPEG和DWT的JPEG2000)、变换相同编码方式不同(如基于DWT的JPEG2000和SPIHT)和量化方式不同(基于标量的SPIHT和基于网格编码量化的QTCQ)。在详细分析实验数据的基础上,得出如下结论:在低比特率时,基于DWT变换的图像压缩算法对掌纹CompCode识别性能影响小于基于DCT的方法;在高比特率时,基于DCT的图像压缩方法对掌纹CompCode识别性能的影响小于基于DWT的。这一结论表明:有损压缩对掌纹CompCode影响并不总和图像率失真程度一致,传统的基于均方误差的评价有损图像压缩方式不适合评估生物特征图像。
     4、研究高分辨率掌纹图像的有损压缩安全编解码。高分辨率掌纹图像具有复杂的几何纹理结构,而传统的小波由于方向有限无法稀疏表示,因而也难以进行高效的压缩编码。对偶树小波变换有6个方向且具有近似平移不变性,能较好地表示掌纹图像的方向纹理特征,然而,其在表示图像时方向依然有限。DFB可获得更加灵活的图像方向表示,因此,提出了在对偶小波树变换的高频子带用DFB进一步分解的算法,并用噪声整形技术对分解得到的系数稀疏化以获得更高的非线性逼近效果。接着,对整形后小波系数重新交织,使相邻的子带系数具有类似小波的父子关系,便于SPIHT压缩编码。实验结果表明,该编码算法在较低比特率下解码图像具有较高的峰值信噪比和视觉效果。结合基于NDF的安全随机算术编码,提出了一种可伸缩的掌纹图像加密算法。SPIHT算法在重构小波域的四叉树过程中,很容易发生雪崩效应,即使当前有一比特发生错误,也将导致整个后续码流都无法正确解码,因此具有很高的安全性。安全算术编码在压缩编码系统的最后一级,能够在不改变图像编码框架的基础上增添安全功能,便于软硬件系统实现扩展。
     5、为解决不同的掌纹在不同应用场合存在的交叉匹配问题,提出了一种加密域匹配认证方案。为了获得较好的认证效果,采用多个方向的Gabor滤波器提取掌纹图像纹理特征,并且在匹配分数层对各个方向的匹配分数用Sum规则融合。利用双NDF产生混沌流密码加密掌纹特征,解决了掌纹模板被盗用时无法撤销和更新的问题。详细分析了在用户密码被盗的情况下,系统性能的退化情况。综合密钥存在与被盗时系统表现出的性能指标,给出了如何设置安全掌纹认证系统的阈值,并讨论了该系统的可撤销和更新能力。
As the rapid development of information and network technology, information security has become increasingly important. Compared with other biometric traits, palmprint has the advantages of large palm area for feature extraction, the simplicity of data collection and high user acceptability. Therefore, palmprint recognition has attracted a lot of researchers' attention both home and abroad.However, the palmprint authentication system itself has inherent security threats, such as biological images and the template does not have the secret of openness (Uusually, the biometric recognition algorithms are public), and there is very little study of the domestic and foreign concerns.
     In this paper, foucsing on the security technology of palmprint authentication, the image compression on recognition performance impact is investigated, and furthermore the conclusions are employed to conduct a technical reference on how to choose image compression methods for both loss and lossless palmprint image compression. Specific tasks are as follows:
     In chapter 1, a systematic analysis of palmprint image compression, encryption and palmprint template protections has been described.
     In chapter 2, the evaluation of security palmprint authentication system is given and the possibility of using chaotic cryptography to protect palmprint template is analyzed. Nonlinear Dynamics Filter has a very good security and characters for implementing in parallel. The nonlinear dynamic filter and its variations are given in the following applications:an efficient stream cipher design, as well as the secure arithmetic coding and Exp-colomb coding applications. Compared with the original stream ciphers, secure Exp-colomb coding method has a high coding efficiency and security arithmetic coding can easily lead to error propagation, which has a high safety.
     In chapter 3, lossless palmprint images compression of the secure storage problems are studied. First of all analysis and test popular lossless image compression algorithms, including those based on transformation (integer achieved JPEG and JPEG2000, as well as the SP-based transform coding method), based on predictive lossless compression algorithms (LJPEG, CALIC and JPEG-LS), dictionary-based compression methods (png and UHA). By testing, analysis and comparison, the JPEG-LS is suitable for lossless palmprint image compression is pointed out for its compression efficiency and speed. Combined with existing secure Exp-colomb encoding algorithm, a secure image scheme based on JPEG-LS is proposed. The encryption algorithm is the image obtained with the incomprehensible nature of the encryption with high efficiency and security.
     In chapter 4, the impact of using different lossy compression algorithms on the matching accuracy of palmprint recognition systems is investigated, including the the image transform, quantization strategies and coding methods employed in the compression process. Further, through the tests conducted on one of the state-of-the-art palmprint recognition algorithms-CompCode, the image compression on the impact of the palmprint recognition performance is discussed detailly and stated. In addition to that we have found PSNR to be not at all suited to predict the recognition performance in iris recognition systems. For high compression rates>15, the DWT-based compression methods such JPEG2000, SPIHT are well suited to be employed in iris recognition systems. In contrary, the JPEG shows an exciting results/performance.
     In chapter 5, to represent the highresolution palmprint image with rich orientational texture more effectively, we use directional filter banks to decompose the subbnad of Dual-tree Discrete Wavelet Transform for more and flexible orientations.Experiments show that the proposed scheme provides high efficient representations for palmprint images. Secure storage problems of the high-resolution palmprint images in the context of lossy compression are studied. Using of efficient SPIHT coding, combined with secure arithmetic coding, a scalable palmprint image encryption algorithm is proposed. The adavantage of secure arithmetic coding in the last stage is that even without changing the image coding framework, the provision of security features is very easy to extend, as well as ease of hardware extensions.
     In chapter 6, to address cross-matching and palmprints template case can not be removed and updated in the token-stolen case, a certified encryption domain matching of dual-factor authentication scheme is presented. Compared with the original palmprint templates, the cancelable ones can strengthen he discriminatory power of palmprints from different hands by increasing the inter-class divergence of different palms more effectively while maintaining the intra-class distance among palmprints of the same hands. At last, the matching stage is directly performed on the encryption domain in parallel to accelerate matching and to protect user's privacy. The final score is obtained by fusing the different directional matching scores via a SUM rule, in which not only is the speed accelerated, but the performance is improved as well.
引文
[1]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年9月出版
    [2]A K Jain, A Ross, S Prabhakar. An introduction to biometric recognition. IEEE trsactionson Circuits and Systems for video Technology, Speeial Issue on Image and video Based Biometric.2004.14(1):4-20.
    [3]D. Zhang, Automated Biometrics-Technologies and Systems. Boston:Kluwer Academic,2000.
    [4]邬向前,张大鹏,王宽全.掌纹识别技术,科学出版社,2006年10月出版
    [5]D. Zhang, W.K. Kong, J. You and M. Wong, On-line palmprint identification, IEEE Trans. Pattern Analysis and Machine Intelligence,2003,25(9):1041-1050.
    [6]J Bradley, CM Brislawn, T Hopper. Wavelet Scalar Quantization Grayscale Fingerprint Comp ression Specification [M]. FB Ⅰ,1996.
    [7]田捷,杨鑫,生物特征加密技术概述(一),中国自动识别技术,2008(2):98-101
    [8]S. Prabhakar, S. Pankanti, and A. K. Jain, Biometric Recognition:Security and Privacy Concerns, IEEE Security and Privacy Magazine,2003,1 (2):33-42
    [9]Muhammad Khurram Khan, Research on Enhancing the Security and Privacy of Biometrics Systems,西南交通大学博士学位论文,2006年10月。
    [10]李鹏,田捷,杨鑫,时鹏,张阳阳,生物特征模版的保护,软件学报2009,20(6):1553-1574.
    [11]N. Ratha, J. Connell and R. Bolle, Enhancng security and privacy in biometric-based authentication systems, IBM Systems Journal,2001,40(3):614-634.
    [12]J. Daugman, The Importance of Being Random:Statistical Principles of Iris Recognition, Pattern Recognition,2003,36(2):279-291
    [13]N.K. Ratha, S. Chikkerur, J.H. Connell et,al, Generating cancelable fingerprint templates, IEEE Trans. PAMI,2007,29(4):561-572.
    [14]Anil K. Jain, Karthik Nandakumar, Abhishek Nagar, Biometric template security, EURASIP Journal on Advances in Signal Processing,2008, p.1-17, January 2008 [doi>10.1155/2008/579416]
    [15]A. K. Ross, J. Shah, and A. K. Jain, From Templates to Images:Reconstructing Fingerprints From Minutiae Points, IEEE Transactions on Pattern Analysis and Machine Intelligence,2007. 29(4):544-560
    [16]K.H. Cheung, A. Kong, D. Zhang, M. Kamel, J. You, T.H.W. Lam, An analysis on accuracy of cancellable biometrics on biohashing, in:Proceedings of the 9th International Conference on Knowledge-based Intelligent Information and Engineering System,2005, pp.1168-1172.
    [17]冈萨雷斯(美)译者:阮宇智阮秋琦数字图像处理(第2版)出版社:电子工业出版社,2007年 8月出版
    [18]G,Lakhani,Modified JPEG Huffman Coding. IEEE Trans. Image Processing,2003,12 (2):159-1697
    [19]LH. Witten, R.M. Neal, J.G Cleary, Arithmetic Coding for Data Compression, Commun. ACM 1987,6(30):520-540
    [20]Liang and T. D. Tran, Fast multiplierless approximation of the DCT with the lifting scheme, IEEE Transaction on Signal Processing,2001,49(12):3032-3044
    [21]S.W.golomb, Run-length encoding, IEEE Trans on information Theory,1996,12(3),399-401
    [22]M.Weinberger, G.Serouss, G.Sapiro. The LOCO-I lossless image compression algorithm:principles and standardization into JPEG-LS. HPL-98-193, Nov.1998.
    [23]J.Ziv and A.Lempel, A universal algorithm for sequential data compression, information Theory, IEEE Trans on information Theory,1977, IT-23(3):337-343
    [24]J.Ziv and A.Lempel, Compression of individual sequences via variable-rate coding, IEEE Trans on information Theory,1978,IT-24(5):530-536
    [25]T.A.Welch, A technique for high-performance data compression, Computer,1984,17(6)8-18.
    [26]Howard. P.G.Vitter.J. S. Fast and efficient lossless image compression. In Storer. IEEE Computer Society J. A. and Cohn. M.. Proc.Press. Los Alamitos. Data Compression Conf.CA,1993.
    [27]X.L.Wu, N.Memon. Context-based, adaptive, lossless image coding. IEEE Trans. Communications,1997,45(4):437-444
    [28]W. Sweldens. The lifting scheme:A custom-design construction of Biorthogonal Wavelets. Appl. Comput. Harmon, Anal,1996
    [29]L.Daubechies, W.Sweldens. Factoring wavelet transforms into lifting step. Journal of Fourier Analysis and Applications,1998,4(3):245-269
    [30]M.Rabbani and R.Joshi. An overview of the JPEG2000 still image compression standard. Signal Processing Image Communication,2002,1(17):348
    [31]J. Liang and T. D. Tran, Approximating the DCT with the Lifting Scheme:Design and Applications, Proc. of the 34th IEEE Asilomar Conference on Signals, Systems, and Computers, Vol.1, pp. 192-196, Pacific Grove, CA, Nov.2000.
    [32]G.K. Wallace. The JPEG still picture compression standard. Communications of the ACM, 1991,34(4)30-44
    [33]C. Christopoulos, A. Skodras, T. Ebrahimi. The JPEG2000 still image coding system:an overview. IEEE Trans.on Consumer Electronics,2000,46(4):1103-1127
    [34]S. Srinivasan. C. Tu, Z. Zhou, D. Ray, S. Regunathan and G. Sullivan, An introduction to the HD Photo technical design, JPEG document wgln4183, Apr.2007.
    [35]J. M. Shapiro. Embedded image coding using zerotrees of wavelet coefficient Trans. on Signal Processing,1993,41(12):34453462.
    [36]A. Said and YV. Pearlman. A New,Fast, and Efficient Image Codec Based on Set Partitioning in
    Hierarchical Trees. IEEE Trans. Ciucuits Syst.& Vedio Technol,1996,6 (3):243-250.
    [37]David Taubman. High Performance Scalable Image Compression with EBCOT. IEEE Trans. on Image Processing,2000,9 (7):1158-1170.
    [38]C.Tian, S.Hemami. An embedded image coding system based on tarp filter with classification. Proceedings of IEEE Int. Conf. Acoustics, Speech, and Signal Process., Montreal,Quebec, Canada, 2004.
    [39]Z.Xiong, K.Ramchandran, M.Vetterli. Space-frequency quantization for wavelet image coding. IEEE Trans.on Image Processing,1997,6(5):677-693.
    [40]A.Brian Banister and Thomas R. Fischer, Quadtree Classification and TCQ Image Coding, IEEE Trans. Ciucuits Syst.& Vedio Technol,2001,11(1):3-8
    [41]B A Olshausen, D J Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature,1996,381(6583):607-609
    [42]M.N.Do,M.Vetterli. The contourlet transform:an efficient directional multiresolution image representation. IEEE Trans.on Image Processing,2005,14(12):2091-2106.
    [43]R H Bamberger, M J T Smith. A filter bank for the directional decomposition of images:theory and design. IEEE Trans. Signal Process.,1992,40(4):882-893.
    [44]M.N.Do, M.Vetterli. Pyramidal directional filter banks and curvelets. Proceedings of IEEE Int. Conf. Image Process., Thessaloniki, Greece,2001.
    [45]Y.Lu and M.N.Do, Lu Y, Do M N. CRISP-contourlets:a critically sampled directional multiresolution image representation. Proceedings of SPIE Conf. Wavelet Appl. in Signal and Image Process.,San Diego, USA,2003.
    [46]R.Eslami,H.Radha. Wavelet-based contourlet transform and its application to image coding. ICIP, 2004, (5):3189-3192.
    [47]R.Eslami,H.Radha. Wavelet-based contourlet coding using an SPIHT-like algorithm. Conf.on Information Sciences and Systems (CISS),2004, pp.784-788
    [48]R.Eslami,H.Radha.Eslami R, Radha H. A new family of nonredundant transforms using hybrid wavelets and directional filter banks. IEEE Trans. Image Process.,2007,16(4):1152-1167.
    [49]T T Nguyen, S Oraintara.Nguyen T T, Oraintara,Multiresolution Direction Filterbanks:Theory, Design, and Applications, IEEE Trans. Signal Process,2005,53(10):3895~3905
    [50]T T Nguyen, S Oraintara. A class of multiresolution directional filter banks. IEEE Trans. Image Process,2007,55(3):949-961.
    [51]Y. Lu and M. N. Do, A new contourlet transform with sharp frequency localization.Proc. IEEE International Conference on Image Processing, Atlanta,2006
    [52]Liu Y, Nguyen T T, Oraintara S. Low bit-rate image coding based on pyramidal directional filter banks. Proceedings of IEEE Int. Conf. Acoustics, Speech, Signal Process., Toulouse,France,2006 [53] Liu Y, Nguyen T T, Oraintara S. Embedded image coding using quincunx directional filterbank. Proceedings of IEEE Int. Symp. Circuits Syst., Island of Kos, Greece,2006.
    [54]Kingsbury N G. Complex wavelets for shift invariant analysis and filtering of signals. Applied Computational Harmonic Analysis,2001,10(3):234-253.
    [55]Selesnick I W, Baraniuk R G, Kingsbury N G. The dual-tree complex wavelet transform. IEEE Signal Process. Mag.,2005,22(6):123-151.
    [56]T. H. Reeves and N. G. Kingsbury, Overcomplete image coding using iterative projection-based noise shaping, in Proc. Of Int. Conf. Image Processing, New York, Sep.2002:597-600.
    [57]J.Y.Yang, J.Z.Xu, F.Wu, Q.H.Dai, Y.Wang. Image coding using 2-D anisotropic dual-tree discrete wavelet transform. Proceedings of IEEE International Conference on Image Processing, San Antonio, USA, Sep.2007:165-168.
    [58]J.Y.Yang, Yao.W, W.L.Xu, Q.H.Dai. Image coding using dualtree discrete wavelet transform. IEEE Transactions on Image Processing,2008,17(9):1555-1569.
    [59]Piella G, Heijmans H J A M. Adaptive lifting schemes with perfect reconstruction. IEEE Trans. Signal Process.,2002,50(7):1620-1630.
    [60]Taubman D. Adaptive, non-separable lifting transforms for image compression. Proceedings of IEEE Int. Conf. Image Process., Kobe, Japan,1999.
    [61]Gerek O N, Cetin A E. A 2-D orientation-adaptive prediction filter in lifting structures for image coding. IEEE Trans. Image Process.,2006,15(1):106-111.
    [62]Ding W, Wu F, Li S. Lifting-based wavelet transform with directionally spatial prediction. Proceedings of Picture Coding Symp., San Francisco, USA,2004.
    [63]Chang C, Girod B. Direction-adaptive discrete wavelet transform for image compression. IEEE Trans. Image Process.,2007,16(5):1289-1302.
    [64]Chappelier V, Guillemot C. Oriented wavelet transform for image compression and denoising. IEEE Trans. Image Process.,2006,15(10):2892-2903.
    [65]G.Peyre,S.Mallat. Surface compression with geometric bandelets. ACM Trans.on Graphics,2005, 24(3):601-608.
    [66]孙文方,赵亦工,宋蓓蓓,基于第二代Bandelets变换的静止图像压缩,西安交通大学学报,2006,40(8),pp.950-954.
    [67]W.Ding, F.Wu, X.Wu, S.Li,H.Li. Adaptive directional lifting-based wavelet transform for image coding. IEEE Trans. on Image Processing,2007,16(2)416-427.
    [68]V.Velisavljevic, B.Beferull-Lozano, M.Vetterli. Space-frequency quantization for image compression with directionlets. IEEE Trans.on Image Processing,2007,16(7):1761-1773.
    [69]J.-Z. Xu, F. Wu, J. Liang, W. Zhang, Directional lapped transforms for image coding, IEEE Trans. Image Processing, accepted, Feb.2009.
    [70]H. Xu, J. Xu and F. Wu, Lifting-based directional DCT-like transform for image coding, IEEE Trans. On circ. Syst. for Video Technology,2007,10:1325-1335.
    [71]I.Ventura.R.Figueras, P.Vandergheynst, P. Frossard, Low-rate and flexible image coding with redundant representations. IEEE Trans on Image Processing,2006,3(15):726-739
    [72]Y.N.Liu, X.D.Zhu, L.G.Sui, Z.Liu, Morphological Zerotree Compression Coding Based on Integer Wavelet Transform for Iris Image.21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)
    [73]夏勇,田捷,邓翔,等.一种有效的自适应指纹图像压缩算法.计算机学报,1999,22(5)525-528.
    [74]陈书贞,王成儒.基于指纹方向图及形态学膨胀操作的指纹图像压缩算法的研究.计算机工程与应用,2004,22:100-103.
    [75]S. Kasaei, M. Deriche, and B. Boashash, A novel fingerprint image compression technique using wavelet packets and pyramid lattice vector quantization, IEEE Transactions on Image Processing 12(11), pp.1365-1378,2002.
    [76]M. Elad, R. Goldenberg, and R. Kimmel, Low bit-rate compression of facial images.IEEE Trans. on Image Processing,2007,16(9):2379-2383
    [77]O. Bryt and M. Elad.Compression of Facial Images Using the K-SVD Algorithm, Journal of Visual Communication and Image Representation,2008,19(4):270-283.
    [78]J. Daugman and C. Downing, Effects of severe image compression on iris recognition performance,IEEE Trans. On Information Forensics and Security 2008,3(1):52-61.
    [79]S. Rakshit, M. Monro Donald, An Evaluation of Image Sampling and Compression for Human Iris Recognition. IEEE trans on information forensics and security,2007,2(3):605~612.
    [80]S.Matschitsch, M.Tschinder, Andreas Uhl:Comparison of Compression Algorithms' Impact on Iris Recognition Accuracy. ICB 2007:232-241.
    [81]Y.Z. Du, C.Belcher, Z.Zhou and R.Ives Feature correlation evaluation approach for iris feature quality measure, Signal Processing,2010,90(4):1176-1187
    [82]R.W. Ives, D.A.D. Bishop, Y. Du, C. Belcher, Effects of image compression on iris recognition performance and image quality, in:IEEE Workshop on Computational Intelligence in Biometrics: Theory, Algorithms, and Applications,2009.
    [83]Ives, R.W., Broussard, R.P., Kennell, L.R., Soldan, D.L.:Effects of image compression on iris recognition system performance. Journal of Electronic Imaging 17,011-015 (2008), doi:10.1117/1.2891
    [84]S. Matschitsch, M. Tschinder, and A. Uhl. Comparison of compression algorithms' impact on iris recognition accuracy. In S.-W. Lee and S.Z. Li, editors, Proceedings of the 2nd International Conference on Biometrics 2007 (ICB'07), volume 4642 of LNCS, pages 232-241. Springer Verlag, 2007.
    [85]B. Jerabek, P. Schneider, and A. Uhl, Comparison of lossy image compression methods applied to photorealistic and graphical images using public domain sources, Tech. Rep. RIST15/98, Research Institute for Softwaretechnology, University of Salzburg,1998
    [86]Y. Fisher, ed., Fractal Image Compression:Theory and Application, Springer-Verlag, New York, 1995.
    [87]K. Delac, M. Grigic, and S. Grigic, Effects of JPEG and JPEG2000 compression on face recognition, in Proceedings of ICAPR 2005, LNCS 3687, pp.136-145, Springer-Verlag,2005.
    [88]A. Mascher-Kampfer, H. Stogner, and A. Uhl, Comparison of Compression Algorithms'Impact on Fingerprint and Face Recognition Accuracy, in Visual Computing and Image Processing VCIP 07, Proceedings of SPIE Jan.2007,Vol.6508:65080N-1-65050N-10,
    [89]H.Zheng,Y.L.Lu X.F.Feng, improved Compression Algorithm Based on Region of Interest of Face. Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)
    [90]Jutta Hammerle-Uhl, C. Prahauser, T. Starzacher, Andreas Uhl,Improving Compressed Iris Recognition Accuracy Using JPEG2000 RoI Coding, Lecture Notes In Computer Science; Vol. 5558 Proceedings of the Third International Conference on Advances in Biometrics table of contents Alghero, ItalySection:Iris table of contents Pages:1102-1111 Year of Publication: 2009
    [91]F.Han, J.Hu,X.Yu and Wang, Fingerprint images encryption via multi-scroll chaotic attractors, Applied Mathematics and Computation,2006,185(2):931-939.
    [92]M. Podesser, H.-P. Schmidt, and A. Uhl, Selective bitplane encryption for secure transmission of image data in mobile environments, presented at the 5th IEEE Nordic Signal Processing Symp., Tromso-Trondheim, Norway, Oct.2002.
    [93]D. Moon, Y. Chung, S. B. Pan, K. Moon, and K. I. Chung, An efficient selective encryption of fingerprint images for embedded processors, ETRI J.,2006,28(4):444~452
    [94]D.Engel, Elias Pschernig and Andreas Uhl. An Analysis of Lightweight Encryption Schemes for Fingerprint Images. IEEE Transactions on Information Forensics and Security,2008,3 (2): 173~182.
    [95]G.Wu, C.Kuo. Design of Integrated Multimedia Compression and Encryption Systems. IEEE Transaction on Multimedia.2005 7(5):828-839.
    [96]H. Cheng and X. Li, Partial encryption of compressed images and videos, IEEE Trans. Image Process.2000,48(8):2439-2451.
    [97]W. Zeng and S. Lei, Efficient frequency domain selective scrambling of digital video, IEEE Trans. Multimedia,2003,5(1):118-129.
    [98]I. H. Witten and J. G. Cleary, On the privacy afforded by adaptive text compression," Computers and Security,1988,7(4):397-408.
    [99]H. A. Bergen and J. M. Hogan, Data security in a fixed-model arithmetic coding compression algorithm, Comput. Security, vol.11,1992.
    [100]H. A. Bergen and J.M. Hogan, Chosen plaintext attack on an adaptive arithmetic coding compression algorithm," Computers and Security,1993,12(2):157-167.
    [101]J. G. Cleary, S. A. Irvine, and 1. Rinsma-Melchert, On the insecurity of arithmetic coding, Computers and Security,1995,14(2):167-180.
    [102]赵风光,倪兴芳,姜峰.算术编码和数据加密.通信学报,1999,20(4):92-96
    [103]谢冬青,谢志坚,李超,冷健.关于一种算术编码数据加密方案的密码分析.通信学报,2001,22(3):40-45.
    [104]郑浩然,金晨辉.对基于算术编码的一个数据加密算法的已知明文攻击.通信学报,2003,24(11):73-78.
    [105]P. W. Moo and X. Wu, Resynchronization properties of arithmetic coding,in Proc. IEEE Int. Conf. Image Processing,1999.
    [106]R. Bose, S. Pathak, A novel compression and encryption scheme using variable model arithmetic coding and coupled chaotic system. IEEE Trans. Circuits Syst. I:regular papers,2006,53(4):848-857.
    [107]J. T. Zhou and O. C. Au, Comments on'A Novel Compression and Encryption Scheme Using Variable Model Arithmetic Coding and Coupled Chaotic System',IEEE Transactions Circuits and Systems I,2008,55(11):3368-3369.
    [108]J. Wen, H. Kim, J. Villasenor, Binary arithmetic coding with key-based interval splitting, IEEE Signal Processing Letters,2006,13:69-72.
    [109]H. Kim, J.Wen, and J. D. Villasenor, Secure arithmetic coding, IEEE Trans. Signal Process.,2007, (55)5:2263-2272.
    [110]G. Jakimoski and K. Subbalakshmi, Cryptanalysis of some multimedia encryption schemes, IEEE Trans. Multimedia,2008,10(3):330-338.
    [111]J. T. Zhou and O. C. Au, Adaptive Chosen-ciphertext Attack on Secure Arithmetic Coding,IEEE Transactions Signal Processing,2009,57(5):1825-1838.
    [112]Hung-Min Sun, King-Hang Wang, and Wei-Chih Ting, On the Security of the Secure Arithmetic Coding. IEEE Trans. On information forensics and security,2009,4(4):781-789
    [113]M. Grangetto, E. Magli, and G. Olmo, Multimedia selective encryption by means of randomized arithmetic coding,IEEE Trans. Multimedia,2006,8(5):905-917.
    [114]B. Mi, X. Liao and Y. Chen, A novel chaotic encryption scheme based on arithmetic coding, Chaos Solitons, Fractals,2008, (38):1523-1531
    [115]H.J. Li, J.S.Zhang, A secure and efficient entropy coding based on arithmetic coding, Communications in Nonlinear Science and Numerical Simulations 14 (2009) 4304-4318
    [116]J. T. Zhou, Z. Q. Liang, Y. Chen and O. C. Au, Security Analysis of Multimedia Encryption Schemes based on Multiple Huffman Table, IEEE Signal Processing Letters,2007,14(3):201-204.
    [117]S. G. Lian, Z. X. Liu, Z. Ren and H. L. Wang, "Secure Advanced Video Coding based on Selective Encryption Algorithms," IEEE Transactions on Consumer Electronics,2006.52(2) 621-629
    [118]J. T. Zhou and O. C. Au, Secure Exp-golomb Coding using Stream Cipher, In Proceedings of IEEE International Conference on Acoustics. Speech, and Signal Processing,2009.4:1457-1460.
    [119]D. Xie and C.-C. Jay Kuo, Secure Lempel Ziv Compression with Embedded Encryption, In Proceedings of SPIE, pp.318-327, March 2005.
    [120]J. T. Zhou and O. C. Au,Secure Lempel-Ziv-Welch (LZW) Algorithm with Random Dictionary Insertion and Permutation, In Proceedings of IEEE Inter-national Conference on Multimedia and Expo, pp.245-248, June 2008.
    [121]M.S.Baptista. Cryptography with chaos, Physics Letters A,240(1-2):50-54,1998
    [122]K.W.Wong. A fast chaotic cryptographic scheme with dynamic look-up table, Physics Letters A, 298(4):238-242,2002.
    [123]K.W.Wong, S.W.H, C.K.Yung. A chaotic cryptography scheme for generating short ciphertext, Physics Letters A,310(1):67-73,2003.
    [124]Kwok-Wo Wong, Ching-Hung Yuen, Embedding Compression in Chaos-based Cryptography IEEE trans. On circuits and systems-II:Express BRIEFS,2008,55(11):1193-1197.
    [125]Hengjian li, Jiashu zhang, Embedding arithmetic coding in Chaos-based cryptography. Chinese Physics B, Chinese Physics B 2010,19(5):050508-1-050508-9
    [126]Kwok-Wo Wong, Qiuzhen Lin and Jianyong Chen, Simultaneous arithmetic coding and encryption using chaotic maps, IEEE Transactions on Circuits and Systems Ⅱ:Express Briefs.2010,57(2):146-150
    [127]J.G. Daugman, High confidence visual recognition of persons by a test of statistical independence, IEEE Transactions on Pattern Analysis and Machine Intelligence,1993,15(11):1148-1161.
    [128]A. W.-K. Kong, D. Zhang, and W. Li, Palmprint feature extraction using 2-D Gabor filters, Pattern Recognit.,2003,36(10):2339-2347.
    [129]A. Kong, D. Zhang, Feature-level fusion for effective palmprint authentication, in:Proceedings of International Conference on Biometric Authentication,2004,1:520-523.
    [130]W. Kong, D. Zhang, M. Kamel. Palmprint identification using feature-level fusion. Pattern Recognition,2006,39(3):478-487.
    [131]X. Wu, D. Zhang, K. Wang, Fusion of phase and orientation information for palmprint authentication, Pattern Analysis and Applications,2006,9 (2):103-111.
    [132]A.K. Kong, D. Zhang, Competitive coding scheme for palmprint verification, in:Proceedings of the 17th International Conference on Pattern Recognition,2004,520-523.
    [133]Jia W, De-Shuang Huang, David Zhang, Palmprint verification based on robust line orientation code, Pattern Recognition,2008,41:1504-1513.
    [134]F.Yue W.M.Zuo, D.Zhang,等, Orientation selection using modified FCM for CompCode-based palmprint recognition, Pattern Recognition 42 (2009) 2841-2849
    [135]Z. Sun, T. Tan, Y. Wang, S.Z. Li, Ordinal palmprint representation for personal identification, in: IEEE Proceedings.CVPR (2005)279-284.
    [136]张家树;温长芝,基于二维正交Log-Gabor滤波的高精度掌纹识别方法,发明申请号:CN200810044611.0发明专利授权号:ZL200810044611.0
    [137]Z.H Guo, D.Zhang, L.Zhang,等,Palmprint verification using binary orientation co-occurrence vector, Pattern Recognition Letters,30 (2009) 1219-1227
    [138]张家树;黄文辉,基于独立匹配分数层融合的高精度掌纹识别算法,发明申请号:CN200910059271.3公开号:CN101551857
    [139]De-Shuang Huang, Wei Jia, David Zhang, Palmprint verification based onprincipal lines, Pattern Recognition,2008,.41 (4):1316-1328.
    [140]Pablo H. Hennings-Yeomans, B. V. K. Vijaya Kumar, and Marios Savvides, Palmprint Classification Using Multiple Advanced Correlation Filters and Palm-Specific Segmentation. IEEE Trans. On information forensics and security,2007,2(3):613-712.
    [141]C.Z.Y.Chen, W. F Xie. Pattern recognition with SVM and dual-tree complex wavelets. Image and Vision Computing,2007,25(6):960-966.
    [142]李强,裘正定,孙冬梅,刘陆陆.基于改进二维主成分分析的在线掌纹识别电子学报.2005,33(10):1886-1889.
    [143]W. Zuo, D. Zhang, K. Wang. An assembled matrix distance metric for 2DPCA-based image recognition. Pattern Recognition Letters,2006,27(3):210-216.
    [144]U Uludag, S Pankanti, S Prabhakar, and A K Jain, Biometric cryptosystems:issues and challenges, Proc. of the IEEE, vol.92, no.6, pp.948(?)C960,2004.
    [145]N.K. Ratha, S. Chikkerur, J.H. Connell and R.M. Bolle, Generating cancelable fingerprint templates, IEEE Trans. PAMI,2007,29(4):561-572.
    [146]A.Kong, D.Zhang, K.Mohame, A survey of palmprint recognition, Pattern Recognition,2009, 42(7):1408-1418.
    [147]G. Davida, Y. Frankel, and B. Matt, On enabling secure applictions through off-line biometric identification,IEEE Symposium on Privacy and Security,1998:148-157.
    [148]A Juels and M. Wattenberg, A fuzzy commitment scheme, Sixth ACM Conf. on Comm. Security,1999:28-36,.
    [149]Juels and M. Sudan. A fuzzy Vault Scheme, IEEE International Symposium on Information Theory, 2002.
    [150]T. C. Clancy, N. Kiyavash, and D. J. Lin, Secre smartcard-based fingerprint authentication Proc. ACMSIGMM 2003 Multimedia, Biometrics Methods and Applications Workshop, pp.45-52,2003.
    [151]Y. Dodis,L. Reyzin, and A. Smith, Fuzzy extractors:How to generate strong keys from biometrics and other noisy data,In Proc. Advances in Cryptology-Eurocrypt 2004.
    [152]张凡,冯登国,孙哲南,一种基于模糊提取的虹膜鉴别方案计算机研究与发展,2008,45(6): 1036-1042
    [153]Soutar, D. Roberge, A. Stoinav, G. Gilroy and V. Kumar, Biometric Encryption Using Image Processing,Proc. SPIE,1998,3314:174-188.
    [154]M.Savvides, B. V. K. Vijaya Kumar, K.Khosla Pradeep, Cancelable Biometric Filters for Face Recognition, Int.Conf.Pattern Recognit.2004,3:922-925
    [155]M.Savvides, B. V. K. Vijaya Kumar, K. Khosla Pradeep,Face verification using correlation filters, Proc. Of Third IEEE Automatic Identification Advanced Technologies, Tarrytown, NY,2002:56-61
    [156]F. Monrose, M. K. Reiter and S. Wetzel, Password Hardening Based on Key Stroke Dynamics, Proc. ACM Conf. Computer and Comm. Security,1999,73-82.
    [157]Monrose, M. Reiter, Q. Li and S.Wetzel, Cryptographc Key G eneration from Voice,Proc IEEE Symp. Security and Privacy, pp.202-213, May 2001.
    [158]P. Tuyls and J. Goseling, Capacity and Eamples of Template-Protecting Biometric Authentication Systems,ECCV Workshop BioAW 2004:158-170.
    [159]F.Hao, R.Anderson, J.Daugman, Combining crypto with biometrics effectively. IEEE Trans. on Computers,2006,55(9):1081-1088.
    [160]S.C.Draper, A.Khisti and E.Martinian, A Vetro and J S Yedidia, Using distributed Source coding to secure fingerprint biometric, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing,2007.
    [161]Y.Sutcu, Q.Li and N.Memon, Protecting biometric template with sketch:theory and practice, IEEE Transactions on Information Forensics and Security,2007,2(3)Part2:503-512.
    [162]冯全,苏菲,蔡安妮,生物加密综述,计算机工程,2008,34(10):141-143.
    [163]冯全,苏菲,蔡安妮,一种利用多元线性函数绑定指纹细节点与密钥的新方法,兰州大学学报,2008,44(2):1-3.
    [164]D.Ngo, A.Teoh, and A.Goh, Biometric Hash:High-Confidence Face Recognition, IEEE Transactions onCcircuits and Ssystems for Video Technology, vol.16, no.6,2006.
    [165]A.Teoh, A.Goh, and D. Ngo, Random Multispace Quantization as an Analytic Mechanism for Biohashing of Biometric and Random Identity Inputs, IEEE Transactions on Pattern Analysis and Machine Intelligence,2006,28(12):1892-1901.
    [166]T.Connie, A.Teoh, M.Goh, D.Ngo. PalmHashing:a novel approach for dual-factor authentication Pattern Analysis & Applications, Volume 7, Number3/2004年9月
    [167]T.Connie, A.Teoh, M.Goh, D.Ngo PalmHashing:a novel approach for cancelable biometrics, Information Processing Letters,2005,93:1-5.
    [168]A.Teoh, B.Jin,and D.Ngo C.Ling, Palmprint based Cancelable Biometric Authentication System, International Journal of Signal Processing 1;2 www.waset.org Spring 2005
    [169]A. Kong, K.H. Cheung, D. Zhang, M. Kamel, J. You, An analysis of Biohashing and its variants, Pattern Recognition.2006,39 (7):1359-1368.
    [170]A.Lumini, L.Nammi.An improved Bio Hashing for human authentication. Pattern Recognition, 2007,40:1057-1065.
    [171]A. Kong, D. Zhang, M. Kamel, A study of brute-force break-ins of a palmprint verification system, IEEE Transactions on Systems, Man and Cybernetics, Part B 36 (5) (2006) 1201-1205.
    [172]A. Kong, D. Zhang, M. Kamel, Three measure for secure palmprint. identification, Pattern Recognition.2008,41 (4):1329-1337.
    [173]张家树,基于Log-Gabor混合滤波相位特征加密的高精度掌纹安全识别方法,发明申请号:CN200810044795.0发明专利授权号:ZL2008100447
    [174]X.Q.Wu,D.Zhang, K.Q.Wang, A Palmprint Cryptosystem, International Conference on Biometrics (ICB 2007), Aug.2007.
    [175]X.Q.Wu, D.Zhang, K.Q.Wang, A Cryptosystem based on Palmprint Feature, The 19th IEEE International Conference on Pattern Recognition.2008.
    [176]K.K.Muhammad, J.S.Zhang and L Tian, Chaotic secure content-based hidden transmission of biometric templates, Chaos, Solitons & Fractals,2007,32(5):1749-1759
    [177]K.K.Muhammad, J.S.Zhang, X.M.Wang, Chaotic hash-based fingerprint biometric remote user authentication scheme on mobile devices, Chaos Solitons & Fractals,2008,35 (3):519-524
    [178]Muhammad Khurtam Khan, Jiashu Zhang, Enhaneing the Transmission Seeurity of Contenr-based Hidden Biomerrie Data, ISNN'06, Lecuter Noets in Computer ScieneeL(LNCS),2006 (3973):214~223.
    [179]Muhammad Khurtam Khan, Jiashu Zhang, "Enhaneing the Security of Biometric Templates For Trust Worthy Person Authentication, International transactionon On computer Science&Engineering,2005,6(1)166~176, SouthKorea.
    [180]L. Kocarev. Chaos-based crptograpby:A brief overview. IEEE Circuits and Systems Magazine.2001,1(3):6-21
    [181]R.Matthews On the derivation of a "chaotic" encryption algorithm.1989, Cryptologia 8(1):29-41.
    [182]X.M Wang, J.S Zhang, W.F Zhang, Chaotic keyed hash function based on feedforward-feedback nonlinear digital filter, Physics Letters A,2007,362(5-6):439-448.
    [183]D.Xiao, X.F.Liao, Shaojiang Deng One-way Hash function construction based on the chaotic map with changeable-parameter, Chaos, Solitons and Fractals,2005,24:65-71.
    [184]S. Li, X. Mou, and Y. Cai, Pseudo-random bit generator based on couple chaotic systems and its application in stream-ciphers cryptography, in Progress in Cryptology-INDOCRYPT. Chennai, India:Springer;Verlag, Dec.16-20,(2001)316-329.
    [185]G.M.Bernstein, M.A. Lieberman. Secure random number generation using chaotic circuits, IEEE Trans. Circuits and Systems,1990,37(9):1157-1164.
    [186]S. Lian, J. Sun, J. Wang Z. A chaotic stream cipher and the usage in video protection, Chaos,Solitons and Fractals,2007:851-859.
    [187]Goce Jakimoski and L.jupco Kocarev, Chaos and Cryptography:Block Encryption Ciphers Based on Chaotic Maps. IEEE trans. On circuits and systems-11,2001,48(2)163-169
    [188]Yong Wang, Kwok-Wo Wong, Xiaofeng Liao, Tao Xiang A block cipher with dynamic S-boxes based on tent map, Commun Nonlinear Sci Numer Simulat 14 (2009) 3089-3099
    [189]C.E.Shannon. Communication Theory of Secret Systems. Bell System Technical Journal.1949,28: 656-715.
    [190]王小敏,非线性动力学滤波器设计及其在信息安全中的应用研究,2007,西南交通大学博士论文
    [191]J.Fridricb. Symmetric cipher based on dimensional chaotic maps. International Journal of Bifurcation and Chaos.1998,8.(6):1259-1284.
    [192]邓绍江,混沌理论及其在信息安全中的应用研究,重庆大学博士学位论文,2005.6.
    [193]王继志,王英龙,王美琴,一类基于混沌映射构造Hash函数方法的碰撞缺陷,物理学报,2006,55(10):5048-5054.
    [194]G. Alvarez, S.J. Li. Some Basic Cryptographic Requirements for Chaos-Based Cryptosystems, Int. J. Bifurcation and Chaos,2006,16(8):2129-2151.
    [195]盛利元,孙克辉,李传兵,基于切延迟的椭圆反射腔离散混沌系统及其性能研究,物理学报,2004,53(9):2871-2876.
    [196]N.K.Pareek, V.Patidar, K.K.Sud. Discrete chaotic cryptography using external key, Physics Letters A,2003,309:75-82.
    [197]G.Alvarez, F.Montoya, M.Romera,等.,Cryptanalysis of a discrete chaotic cryptosystem using external key, Physics Letters A,2003,319:334-339.
    [198]G.Alvarez, F.Montoya, M.Pastor,等.,Gryptanalysis of a chaotic encryption system. Physics Letters A,2000,276(1-4):191-196.
    [199]李树钧.数字化混沌密码的分析和设计.西安交通大学博士学位论文,2003.
    [200]L. M. Pecora and T. L. Carroll. Synchronization in chaotic systems. Physical Review Letters, 64(8):821-824,1990.
    [201]V. A. Protopopescu, R. T. Santoro, and J. S. Tollover. Fast and secure encryption-decryption method based on chaotic dynamics. US Patent No.5479513.1995
    [202]D.R.Frey. Chaotic digital encoding:An approach to secure communication, IEEE Trans. Circuits Systs Ⅱ,40(10):660-666,1993
    [203]U.Feldmann. M.Hasler, W.Schwarz. Communication by chaotic signals:The inverse system approach, Int.J. Circuit Theory and Applications,24(5):551-579,1996.
    [204]H.Zhou, X.T.Ling. Problems with the chaotic inverse system encryption approach. IEEE Trans. Circuits and Systems Ⅰ,44(3):268-271,1997
    [205]胡国杰,冯正进.一类数字混加密系统的安全性分析,电子与信息学报,2003,25(11):1514-1518.
    [206]周红,罗杰,凌燮亭,混沌前馈型流密码的设计,电子学报.1998,.26(1):98-101,
    [207]S. Tao.W. Ruili, and Y. Yixun, Perturbance-based algorithm to expand cycle length of chaotic key stream, Electron. Lett.,.34(9) 1998:873-874.
    [208]S. Tao, W. Ruili, and Y. Yixun, Clock-controlled chaotic keystream generators, Electron. Lett., 34(20)1998:1932-1934
    [209]邱跃洪何晨诸鸿文,一种反馈-前馈结构的混沌流密码,西安交通大学学报2002,36(3):309~312
    [210]K.Kelber, N-Dimensional Uniform Probability Distribution in Nonlinear Autoregressive Filter Structures. IEEE Trans on. Circuits and systems-I Fundamental theory and applications 2000,47(9):1413-1417.
    [211]K.Kelber, M.Gotz, W.Schwarz. Generation of chaotic signals with n-dimensional uniform probability distribution by digital filter structures. In Proc. IEEE Digital Signal Processing Workshop,1996.486-489
    [212]NIST Special Publication 800-22, http://csrc.nist.gov/rng/.
    [213]Nagaraj N, Vaidya P, Bhat K. Arithmetic coding as a non-linear dynamical system. Commun Nonlinear Sci Numer Simulat 2009; 14:1013-20.
    [214]黄方军。.基于数字化混沌理论的信息安全研究,华中科技大学博士论文,2005,5..
    [215]Kevin M. Short. Signal extraction from chaotic communications. Int. J. Bifurcation and Chaos, 7(7):1579-1597,1997.
    [216]Andrew T. Parker and.Kevin M. Short. Reconstructing the keystream from a chaotic encryption scheme. IEEE Trans. Circuits and Systems-Ⅰ,48(5):104-112,2001..
    [217]胡汉平,刘双红,王祖喜等,一种混沌密钥流产生方法,计算机学报,27(3):408-412,2004.
    [218]Georg Weinhandel, Herbert Stogner, Andreas Uhl, Experimental Study on Lossless Compression of Biometric Sample Data, In Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis, ISPA'09, Salzburg, Austria, September 16-18,2009
    [219]Nigel M. Allinson, Jeevandra Sivarajah, Ian Gledhill, Michael Carling, and Lesley J. Allinson, Robust Wireless Transmission of Compressed Latent Fingerprint Images, IEEE Trans on information forensics and security,2007,2 (3):331-340
    [220]李文新,夏胜雄等.基于主线特征的双向匹配的掌纹识别新方法.计算机研究与发展.2004,41(6):997-1002.
    [221]杨震群,魏骁勇等.掌纹样本采集技术及预处理技术的分析与研究.计算机应用.2007,27(2):380-383.
    [222]Vandergheynst P, Frossard P. Efficient image representation by anisotropic refinement in matching pursuit. In:Proceedings of IEEE on ICASSP[C]. Salt Lake City, UT, USA,2001, Vol (3):1757~1760.
    [223]Anil K. Jain, Jianjiang Feng, Latent Palmprint Matching IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31 (6):1032-1047.
    [224]Y. Lu and M. N. DoA new contourlet transform with sharp frequency localization.Proc. IEEE International Conference on Image Processing, Atlanta,2006
    [225]V. Chappelier.C. Guillemot,S. Marinkovic. Image coding with iterated contourlet and wavelet transforms.ICIP 2004,2004, pp.3157-3160.
    [226]T. Cooklev,T. Yoshida,A. Nishihara. Maximally flat half-band diamond-shaped FIR filters using the Bernstein polynomial. IEEE Trans. on Circuits and Systems 11,1993, Vol.40(11), pp.749-751
    [227]Liu Y, Nguyen T T, Oraintara S. Low bit-rate image coding based on pyramidal directional filter banks. Proceedings of IEEE Int. Conf. Acoustics, Speech, Signal Process., Toulouse,France,2006.
    [228]Liu Y, Nguyen T T, Oraintara S. Embedded image coding using quincunx directional filterbank. Proceedings of IEEE Int. Symp. Circuits Syst.. Island of Kos, Greece,2006.
    [229]Nason G P, Silverman B. The stationary wavelet transform and some statistical applications. Proceedings of Wavelets in Statistics, Lectures Notes in Statistics,1995.Shannon CE. A mathematical theory of communication. Bell Sys Tech J 1948,27:379-423
    [230]A.L. Cunha,J. Zhou,M.N. Do. The nonsubsampled contourlet transform:theory, design, and applications. IEEE Trans. on Image Processing,2006, Vol.15(10), pp.3089-3101
    [231]Kingsbury N G. The dual-tree complex wavelet transform:a new technique for shift invariance and directional filters. Proceedings of IEEE DSP Workshop, Bryce Canyon,1998
    [232]Selesnick I W. The design of approximate Hilbert transform pairs of wavelet bases. IEEE Trans. Signal Process.,2002,50(5):1144-1152.
    [233]Kingsbury N. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. Proceedings of IEEE Int. Conf. Image Process., Vancouver, BC, Canada,2000.
    [234]Josef Kittler, Mohamad Hatef, Robert P.W. Duin, and Jiri Matas, On Combining Classifiers, IEEE Trans. Pattern Anal. Mach. lntell.1998,20(3):226-239
    [235]Ludmila I. Kuncheva, A Theoretical Study on Six Classifier Fusion Strategies, IEEE Trans. Pattern Anal. Mach. Intell.2002,24(2):281-286