基于JPEG 2000双压缩的图像篡改检测
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摘要
随着计算机和网络技术的快速发展,高分辨率的数码相机以及功能强大的图像编辑软件(如:Adobe Photoshop,Microsoft Photo Editor,CorelDRAW等)的出现,图像篡改已经越来越普遍,而且,篡改后的图像难以辨别真伪。如果将篡改后的图像用于新闻媒体或法庭证物上,将会对社会造成很大的影响。因此对数字图像的真伪鉴别是非常重要的,针对图像篡改的检测,目前已经成为信息领域的研究热点。
本文综述了图像篡改检测的研究现状,并基于JPEG 2000图像压缩标准的良好性能和发展前景,提出了一种基于JPEG 2000双压缩的图像篡改检测算法。文章首先分析了JPEG 2000双压缩时子带DWT系数的统计特性,及其子带DWT系数直方图傅里叶变换的幅频特性,此特性表现为:与一次压缩相比,双压缩时在幅度谱的中高频段存在较大峰值点的现象。本文利用小波变换提取出较大峰值点(奇异点),并计算出较大的峰值点所引起的极差(指极大值和极小值的差值),通过对极差取阈值来判定图像是否经过JPEG 2000二次压缩。其次,文中阐述了被篡改的JPEG 2000图像中篡改区域和未篡改区域可分的依据,并根据此依据提出了定位篡改区域的方法。实验表明,本文提出的算法不仅能有效检测出JPEG 2000双压缩,而且还可对图像的篡改区域进行准确定位。
With the rapid and extensive development of computer and network technique, the emergence of high resolution digital caneras,and sophisticated photo-editing software (such as Adobe Photoshop,Microsoft Photo Editor,CorelDRAW), doctored images can be found anywhere,moreover,they are hard to distinguish from authentic photographs.These forgeries, if used in the mass media or courts of law, can have an important impact on our society. It is very important to detect the doctored images. Therefore the detection of doctored images has became a research focus in the information field.
This dissertation summarizes the research status of tamper detection, and based on the good performance and development prospects of JPEG 2000 image compression standard, this dissertation proposes a method of detecting doctored double JPEG 2000 images. The dissertation analyses the statistics properties of double JPEG 2000 compression, and the artifacts in the Fourier transforms of subband DWT coefficients histogram, that is,compared with the first compression, stronger peaks are visible in the mid and high frequencies. Based on the characteristics of Wavalet transform which can be used to locate the singularity (peaks), then,according to the range(the difference of maximum and minimum),which is induced by the peaks,we propose a method of detecting double JPEG 2000 compression. The dissertation points out that it is divisible of doctored blocks and undoctored blocks, and so a simple and effective method is used to locate the doctored part.The experiments show that this algorithm not only can detect double JPEG 2000 compression, but also can accurately locate the doctored part.
本文综述了图像篡改检测的研究现状,并基于JPEG 2000图像压缩标准的良好性能和发展前景,提出了一种基于JPEG 2000双压缩的图像篡改检测算法。文章首先分析了JPEG 2000双压缩时子带DWT系数的统计特性,及其子带DWT系数直方图傅里叶变换的幅频特性,此特性表现为:与一次压缩相比,双压缩时在幅度谱的中高频段存在较大峰值点的现象。本文利用小波变换提取出较大峰值点(奇异点),并计算出较大的峰值点所引起的极差(指极大值和极小值的差值),通过对极差取阈值来判定图像是否经过JPEG 2000二次压缩。其次,文中阐述了被篡改的JPEG 2000图像中篡改区域和未篡改区域可分的依据,并根据此依据提出了定位篡改区域的方法。实验表明,本文提出的算法不仅能有效检测出JPEG 2000双压缩,而且还可对图像的篡改区域进行准确定位。
With the rapid and extensive development of computer and network technique, the emergence of high resolution digital caneras,and sophisticated photo-editing software (such as Adobe Photoshop,Microsoft Photo Editor,CorelDRAW), doctored images can be found anywhere,moreover,they are hard to distinguish from authentic photographs.These forgeries, if used in the mass media or courts of law, can have an important impact on our society. It is very important to detect the doctored images. Therefore the detection of doctored images has became a research focus in the information field.
This dissertation summarizes the research status of tamper detection, and based on the good performance and development prospects of JPEG 2000 image compression standard, this dissertation proposes a method of detecting doctored double JPEG 2000 images. The dissertation analyses the statistics properties of double JPEG 2000 compression, and the artifacts in the Fourier transforms of subband DWT coefficients histogram, that is,compared with the first compression, stronger peaks are visible in the mid and high frequencies. Based on the characteristics of Wavalet transform which can be used to locate the singularity (peaks), then,according to the range(the difference of maximum and minimum),which is induced by the peaks,we propose a method of detecting double JPEG 2000 compression. The dissertation points out that it is divisible of doctored blocks and undoctored blocks, and so a simple and effective method is used to locate the doctored part.The experiments show that this algorithm not only can detect double JPEG 2000 compression, but also can accurately locate the doctored part.
引文
[1]www.aas.net.cn/qikan/manage/wenzhang/2007-0882.pdf
[2]Jim Adams, Ken Parulski,Kevin Spaulding,Color processing in digital cameras, IEEE Micro,1998,18(6):20~30
[3]Jessica Fridrich,David Soukal,Jan Lukas,Detection of copy-move forgery in digital images,In:Proceedings of Digital Forensic Research Workshop,Cleveland,OH, USA, 2003
[4]Alin C Popescu, Hany Farid, Exposing Digital Forgeries by Detecting Duplicated Image Regions, Technical Report TR2004-515, Department of Computer Science, Dartmouth College, 2004
[5]Li Guohui,Wu Qiong,Tu Dan,et al,A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD,In: Proceedings of 2007 IEEE International Conference on Multimedia and Expo, Beijing, China: IEEE, 2007,1750~1753
[6]H.Farid, Exposing Digital Forgeries in Scientific Images, ACM Multimedia and Security Workshop, Geneva, Switzerland, 2006
[7]Popescu Alin C and Farid Harry, Exposing digital forgeries by detecting traces of re-sampling, IEEE Transactions on Signal Processing, 2005, 53(2):758~767
[8]朱秀明,宣国荣和姚秋明等,信息取证中图像重采样检测,计算机应用,2006, 26(11):2596~2597
[9]Popescu Alin C, Statistical Tools for Digital Forensics [Ph.D.dissertation], Department of Computer Science, Darmouth College, 2005
[10]Fridrich J, Lukas J, Estimation of Primary quantization matrix in double compressed JPEG images, In: Proceedings of Digital Forensic Research Workshop, Cleveland, OH, USA, 2003
[11]戴蒙,林家骏和毛家发,JPEG二次压缩的分析与检测,中国图象图形学报,2006,11(11):1619~1622
[12]Junfeng He,Zhouchen Lin and Lifeng Wang,et al,Detecting Doctored JPEG Images Via DCT Coeffficient Analysis,In:Proceedings of 9th European Conference Computer Vision,Graz,Austria,2006,423~435
[13]Micah K. Johnson and Hany Farid, Exposing digital forgeries by detecting inconsistencies in lighting, In: Proceedings of the 7th Workshop on Multimedia and Security, New York, NY, USA, 2005, 1~10
[14]Micah K. Johnson andHany Farid, Exposing digital forgeries through specular highlights on the eye,In:Proceedings of the 9th International Workshop on Information Hiding,Saint Malo,France,2007,311~325
[15]Dhruv Mahajan,Ravi Ramamoorthi and Brian Curless,A theory of frequency domain invariants:spherical harmonic identities for BRDF/lighting transfer and image consistency,IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2): 197~213
[16]Dun-Yu Hasio and Soo-Chang Pei,Detecting digital tampering by blur estimation, In:Proceedings of First International Workshop on Systematic Approaches to Digital Forensic Engineering,Taipei,China:IEEE,2005,264~278
[17]王波,孙璐璐,孔祥维等,图像伪造中模糊操作的异常色调率取证技术,电子学报,2006,34(12A):2451~2454
[18]Y. Sutcu,B. Coskun and H.T. Sencar,et al,Tamper detecting based on regularity of wavelet transform coefficients,In:Proceedings of 2007 IEEE International Conference on Image Processing ,San Antonio,TX,USA:IEEE, 2007,397~400
[19]Alin C Popescu and Hany Farid,Exposing digital forgeries in color filter array interpolated images,IEEE Transactions on signal Processing,2005, 53(10):3948~3959
[20]Yangjing Long, Yizheng Huang, Imaged based source camera identification using demosaicking, In: Proceedings of 8th Workshop on Multimedia Signal Processing, Victoria, BC: IEEE, 2006, 419~424
[21]Ashwin Swaminathan,Min Wu and K.J.Ray Liu,Image tampering identification using blind deconvolution,2006 IEEE International Conference on Image Processing, Atlanta,GA:IEEE,2006,2309~2312
[22]Micah K. Jonhnson and Hany Farid, Exposing digital forgeries through chromatic aberration, In: Processing of the 8th Workshop on Multimedia and Security, Geneva, Switzerland: IEEE, 2006, 48~55
[23]Lukas Jan, Fridrich Jessica and Goljan Miroslav,Detecting digital image forgeries using sensor pattern noise,In:Proceedings of the SPIE,2006,6072:362~372
[24]Yu-Feng Hsu and Shih-Fu Chang, Detecting image splicing using geometry invariants and camera,In:Proceedings of 2006 IEEE International Conference on Multimedia and Expo,Toronto,Ont:IEEE,2006,549~552
[25]Zhouchen Lin,Rongrong Wang and Xiaoou Tang,et al,Detecting doctored images using camera response normality and consistency analysis,In:Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recongnition, San Diego,CA,USA:IEEE,2005,1087~1092
[26]Siwei Lyu and Hany Farid,How realistic is photorealistic? IEEE Transactions an Signal Processing,2005,53(2):845~850
[27]Siwei Lyu,Natural Image Statistics for Digital Image Forensics[Ph.D.dissertation], Department of Computer Science,Darthmouth College,2005
[28]Tian Tsong Ng and Shi-Fu Chang, A model for image splicing, In: Proceedings of 2004 International Confenence on Image Processing, Singapore: IEEE, 2004, 1169~1172
[29]Tian-Tsong Ng and Shih-Fu Chang,Blind Detection of Digital Photomontage Using Higher Order Statistics,Advent Technical Report #201-2004-1,Columbia University,June 2004
[30]Sevinc Bayram, Ismail Avcibas and Biilent Sankur B, Image manipulation detection with binary similarity, In: Proceedings of 13th European Signal Processing Conference Antalya, 2005, 752~755
[31]Sevinc Bayram, Ismail Avcibas and Sankur B, Image manipulation detection, Journal of Electronic Imaging, 2006, 15(4), 041102
[32] A.C.Popescu and H.Farid, Statistical Tools for Digital Forensics,6th International Workshop on Informational Hiding,128-147,Toronto,Canada, 2004
[33] Tomá? Pevny and Jessica Fridrich,Eatimation of Primary Quantizaiton Matrix for Steganalysis of Double-Compressed JPEG images,Proceeding of SPIE 6819, 681911 (2008)
[34]C.Chen and Y.Q.Shi, Steganalyzing Texture Images, IEEE ICIP2007 [35D.Fu,Y.Q.Shi and Q.Su,A generalized Benford’s law for JPEG coefficients and its applications in image forgensics,In E.Delp and P.W. Wong,editors,Proceedings of SPIE Electronic Imaging,Security and Watermarking of Multimedia Contents IX,volume 6505,pages 1L1-1L11,2007
[36]张春田,苏育挺和张静,数字图像压缩编码,清华大学出版社,2006-01
[37]刘涛,曾祥利和曾军,实用小波分析入门,国防工业出版社,2006-04
[2]Jim Adams, Ken Parulski,Kevin Spaulding,Color processing in digital cameras, IEEE Micro,1998,18(6):20~30
[3]Jessica Fridrich,David Soukal,Jan Lukas,Detection of copy-move forgery in digital images,In:Proceedings of Digital Forensic Research Workshop,Cleveland,OH, USA, 2003
[4]Alin C Popescu, Hany Farid, Exposing Digital Forgeries by Detecting Duplicated Image Regions, Technical Report TR2004-515, Department of Computer Science, Dartmouth College, 2004
[5]Li Guohui,Wu Qiong,Tu Dan,et al,A sorted neighborhood approach for detecting duplicated regions in image forgeries based on DWT and SVD,In: Proceedings of 2007 IEEE International Conference on Multimedia and Expo, Beijing, China: IEEE, 2007,1750~1753
[6]H.Farid, Exposing Digital Forgeries in Scientific Images, ACM Multimedia and Security Workshop, Geneva, Switzerland, 2006
[7]Popescu Alin C and Farid Harry, Exposing digital forgeries by detecting traces of re-sampling, IEEE Transactions on Signal Processing, 2005, 53(2):758~767
[8]朱秀明,宣国荣和姚秋明等,信息取证中图像重采样检测,计算机应用,2006, 26(11):2596~2597
[9]Popescu Alin C, Statistical Tools for Digital Forensics [Ph.D.dissertation], Department of Computer Science, Darmouth College, 2005
[10]Fridrich J, Lukas J, Estimation of Primary quantization matrix in double compressed JPEG images, In: Proceedings of Digital Forensic Research Workshop, Cleveland, OH, USA, 2003
[11]戴蒙,林家骏和毛家发,JPEG二次压缩的分析与检测,中国图象图形学报,2006,11(11):1619~1622
[12]Junfeng He,Zhouchen Lin and Lifeng Wang,et al,Detecting Doctored JPEG Images Via DCT Coeffficient Analysis,In:Proceedings of 9th European Conference Computer Vision,Graz,Austria,2006,423~435
[13]Micah K. Johnson and Hany Farid, Exposing digital forgeries by detecting inconsistencies in lighting, In: Proceedings of the 7th Workshop on Multimedia and Security, New York, NY, USA, 2005, 1~10
[14]Micah K. Johnson andHany Farid, Exposing digital forgeries through specular highlights on the eye,In:Proceedings of the 9th International Workshop on Information Hiding,Saint Malo,France,2007,311~325
[15]Dhruv Mahajan,Ravi Ramamoorthi and Brian Curless,A theory of frequency domain invariants:spherical harmonic identities for BRDF/lighting transfer and image consistency,IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2): 197~213
[16]Dun-Yu Hasio and Soo-Chang Pei,Detecting digital tampering by blur estimation, In:Proceedings of First International Workshop on Systematic Approaches to Digital Forensic Engineering,Taipei,China:IEEE,2005,264~278
[17]王波,孙璐璐,孔祥维等,图像伪造中模糊操作的异常色调率取证技术,电子学报,2006,34(12A):2451~2454
[18]Y. Sutcu,B. Coskun and H.T. Sencar,et al,Tamper detecting based on regularity of wavelet transform coefficients,In:Proceedings of 2007 IEEE International Conference on Image Processing ,San Antonio,TX,USA:IEEE, 2007,397~400
[19]Alin C Popescu and Hany Farid,Exposing digital forgeries in color filter array interpolated images,IEEE Transactions on signal Processing,2005, 53(10):3948~3959
[20]Yangjing Long, Yizheng Huang, Imaged based source camera identification using demosaicking, In: Proceedings of 8th Workshop on Multimedia Signal Processing, Victoria, BC: IEEE, 2006, 419~424
[21]Ashwin Swaminathan,Min Wu and K.J.Ray Liu,Image tampering identification using blind deconvolution,2006 IEEE International Conference on Image Processing, Atlanta,GA:IEEE,2006,2309~2312
[22]Micah K. Jonhnson and Hany Farid, Exposing digital forgeries through chromatic aberration, In: Processing of the 8th Workshop on Multimedia and Security, Geneva, Switzerland: IEEE, 2006, 48~55
[23]Lukas Jan, Fridrich Jessica and Goljan Miroslav,Detecting digital image forgeries using sensor pattern noise,In:Proceedings of the SPIE,2006,6072:362~372
[24]Yu-Feng Hsu and Shih-Fu Chang, Detecting image splicing using geometry invariants and camera,In:Proceedings of 2006 IEEE International Conference on Multimedia and Expo,Toronto,Ont:IEEE,2006,549~552
[25]Zhouchen Lin,Rongrong Wang and Xiaoou Tang,et al,Detecting doctored images using camera response normality and consistency analysis,In:Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recongnition, San Diego,CA,USA:IEEE,2005,1087~1092
[26]Siwei Lyu and Hany Farid,How realistic is photorealistic? IEEE Transactions an Signal Processing,2005,53(2):845~850
[27]Siwei Lyu,Natural Image Statistics for Digital Image Forensics[Ph.D.dissertation], Department of Computer Science,Darthmouth College,2005
[28]Tian Tsong Ng and Shi-Fu Chang, A model for image splicing, In: Proceedings of 2004 International Confenence on Image Processing, Singapore: IEEE, 2004, 1169~1172
[29]Tian-Tsong Ng and Shih-Fu Chang,Blind Detection of Digital Photomontage Using Higher Order Statistics,Advent Technical Report #201-2004-1,Columbia University,June 2004
[30]Sevinc Bayram, Ismail Avcibas and Biilent Sankur B, Image manipulation detection with binary similarity, In: Proceedings of 13th European Signal Processing Conference Antalya, 2005, 752~755
[31]Sevinc Bayram, Ismail Avcibas and Sankur B, Image manipulation detection, Journal of Electronic Imaging, 2006, 15(4), 041102
[32] A.C.Popescu and H.Farid, Statistical Tools for Digital Forensics,6th International Workshop on Informational Hiding,128-147,Toronto,Canada, 2004
[33] Tomá? Pevny and Jessica Fridrich,Eatimation of Primary Quantizaiton Matrix for Steganalysis of Double-Compressed JPEG images,Proceeding of SPIE 6819, 681911 (2008)
[34]C.Chen and Y.Q.Shi, Steganalyzing Texture Images, IEEE ICIP2007 [35D.Fu,Y.Q.Shi and Q.Su,A generalized Benford’s law for JPEG coefficients and its applications in image forgensics,In E.Delp and P.W. Wong,editors,Proceedings of SPIE Electronic Imaging,Security and Watermarking of Multimedia Contents IX,volume 6505,pages 1L1-1L11,2007
[36]张春田,苏育挺和张静,数字图像压缩编码,清华大学出版社,2006-01
[37]刘涛,曾祥利和曾军,实用小波分析入门,国防工业出版社,2006-04